Did you know that “On average, large IT projects run 45 percent over budget”? Even more, the same study by McKinsey & Company tells us that software projects are the most prone to cost overruns of all IT work.

There are many reasons why it’s difficult to control budgeting for software development projects. Most of these factors are tied directly to the financial burden of hiring full-time employees for all your IT needs.

An over-reliance on in-house software talent can lead to exuberant overhead costs, rising labor expenses, and unchecked budget overages. Conversely, outsourcing reduces the high costs of hiring in-house, especially in expensive regions like the United States.

In-House Development Challenges

When you hire full-time IT support, you commit your organization to financial burdens that can quickly compound with time.

High Overhead Costs

In-house development requires substantial spending on infrastructure, including office space, facilities, hardware, software licenses, and utilities. Spiceworks explains that “companies typically allocate between 29% and 35% of their IT budget towards hardware.” Since enterprises exceeding $1 billion in revenue spend approximately 2% of their revenue on IT, they incur $7 million annually in hardware expenses alone!

Regulatory requirements like HIPAA, GDPR, PCI DSS, and SOC 2 necessitate specialized tools like data encryption software and IAM systems and require IT teams to obtain certifications like CISSP, CISA, and CompTIA Security+. Deloitte shows that compliance costs for financial service providers have increased by over 60% since the 2008 financial crisis.

Labor Expenses

Hiring specialized talent for in-house software development can be prohibitively expensive, especially in high-demand fields like AI and blockchain. Competitive salaries, recruitment fees, and ongoing training costs quickly add up. These challenges are amplified in regions with limited talent pools and a high cost of living — such as New York and London.

Average annual salaries for software engineers in key markets include:

• Amsterdam: $204,673
• San Francisco: $170,000
• London: $170,000

Budget Overruns

In-house software projects are prone to budget overruns due to scope creep, misaligned priorities, and unforeseen technical challenges. Limited expertise in cost estimation and inefficient workflows also lead to inflated expenses. These overruns can reduce ROI and strain financial resources — to the point of catastrophe. As McKinsey & Company explains, “17 percent of IT projects go so bad that they can threaten the very existence” of businesses.

Cost-Efficiency Through Outsourcing

By outsourcing IT support, your organization avoids long-term financial commitments and benefits from a flexible, cost-effective solution.

Reduced Operational Costs

Outsourcing software development eliminates heavy infrastructure investments like office space, hardware, and compliance. By leveraging outsourced teams, businesses can minimize recurring costs and access cutting-edge technology without the burdens of in-house infrastructure. For enterprise-scale organizations, this means saving millions of dollars annually on overhead costs — especially in regulated markets with stringent compliance rules.

Reduced Labor Costs

Outsourcing partners maintain a global talent pool, eliminating the need for costly recruitment, salaries, and training. By leveraging talent from regions with competitive labor costs, companies can bypass high premiums for expertise.

Average annual salaries for software engineers in key outsourcing markets:

• Brazil: $63,300
• Mexico: $64,300
• Ukraine: $59,800

Outsourcing saves you from paying full-time salaries and allows you to tap into regions with competitive labor costs. Software engineers in Ukraine and LATAM are on average 60% more affordable than in places like San Francisco.

Flexible Engagement

Outsourcing offers flexible engagement models for budget control, allowing businesses to align spending with project scope and priorities. Moreover, outsourcing partners bring expertise in cost estimation and efficient workflows that reduce the risk of scope creep and unexpected expenses. As such, your organization can keep IT projects on budget, regardless of scale or difficulty.

Industry Spotlight: Restaurant Tech

The restaurant industry is a major beneficiary of outsourced software development services. For example, Dev.Pro recently partnered with the digital signage and experience platform Raydiant on a large-scale restaurant project. By developing a robust middleware solution, Dev.Pro enabled seamless connections between Raydiant’s digital signage platform and various POS systems.

Raydiant leveraged Dev.Pro’s skilled extension team to rapidly expand POS system support, develop tailored solutions for quick-service restaurants, and implement custom digital signage. This collaboration streamlined complex processes like integrating design, graphics, and engineering. In the end, Dev.Pro’s support helped Raydiant resolve its resource capacity issues with efficiency and ease.

Summary

Software development is inherently complex. Each project is unique, and seemingly simple problems can prove unexpectedly challenging to implement. As such, isn’t the smartest move to eliminate as many variables as possible?

The financial burden of hiring full-time employees makes it difficult to control software development budgets. Conversely, outsourcing reduces overhead, controls labor costs, and prevents budget overruns, offering a cost-effective alternative to relying solely on in-house talent. Ready to accelerate growth with industry-leading outsourced teams? Contact us today!

By Yurii Buchchenko

Restaurants often fail to understand the infrastructural challenges rooted in adopting sound AI practices and effectively integrating the technology that it encompasses. Choosing the right infrastructure for your restaurant chain is critical to successfully integrate AI technologies.

To begin understanding what you need to do, you need to think in terms of how you can get AI technologies properly functioning. Consider these three parts of the problem:

1. Assess your infrastructure: What do you have, and what do you need? A thorough infrastructure assessment needs to gather all relevant information to ensuring proper AI functionality across your locations

2. AI technology: What technologies or approaches are you integrating? Voice ordering, predictive analytics, or supply-related algorithms/technologies will demand different things from your infrastructure. These needs dictate you will need to upgrade your infrastructure or reconsider what you want to implement.

3. Ensuring functionality: When you have assessed your infrastructure and whether it accords with the AI technology you want to adopt, you can begin to figure out whether the current infrastructure can support the operation of the specific AI technology.

Many restaurants often start implementing AI technologies without understanding their infrastructure or the specific requirements of the AI technology. It’s entirely possible that the current infrastructure meets the requirements, and there is no need to change anything — no new servers to buy, no configurations, deployments, etc. This would be a cost-effective approach, but it’s rare.

Adapting your infrastructure vs. purchasing new resources

What do you do if your current infrastructure doesn’t support your requirements to adopt your desired AI technologies? Then you must consider purchasing and installing new resources, or adapting the AI technology to the current resources. Purchasing and installing new resources, believe it or not, is generally cheaper and simpler. Adapting AI technology to the current resources might not even be possible, depending on the chosen technology and how much control you have over it.

If the AI technology is proprietary, you’ll need a special contract with the provider, and they will handle the adaptation for you. If the AI technology is being developed in-house, then you already likely understand that AI development is not simple. Adapting it to specific hardware is even more complex — you’ll need specialized AI skills and experience, and a regular Data Science engineer won’t be enough. You’ll need a specialized machine learning (ML) engineer with hardware expertise.

What to consider when purchasing and implementing new infrastructure for AI adoption

In essence, it’s better to move toward purchasing and installing hardware. But not all restaurants and chains are the same. Here’s what you should consider when purchasing and implementing new infrastructure to support AI technologies.

Choosing the right cloud solutions

To stay flexible, it’s best to prioritize network connectivity. That way, you can ensure good AI performance regardless of the size, number, or configuration of restaurants. From there, all complexity can be shifted to the cloud.

When investing in cloud computing, it’s critical to understand the main risk. That is, if your network connection fails, your business stops at that single point of failure. While this doesn’t happen often, recovery is very quick, which is why restaurants often prefer this approach. The beauty of cloud solutions is that you can use extremely powerful hardware, with maintenance delegated to the cloud provider. AI technologies tend to require this kind of hardware.

Choosing a cloud provider is exceedingly complex, with many nuances that seasoned development teams can help restaurant companies assess to determine the best choice.

The main criteria that companies should look for in cloud solutions as it relates to AI technologies are accuracy and precision, followed by performance and speed. Why accuracy and precision? Because the key difference between traditional software and AI is that AI always operates within a certain level of accuracy. Traditional software will always say “2+2=4,” whereas AI will say, “there’s a 99.999% chance it’s 4.” A simple example: AI voice ordering might recognize native American English accents with 99% accuracy, but might only recognize 10% of native Spanish speakers’ English.

Choosing local hardware instead of cloud solutions

To determine if local hardware is the right approach, you have to consider whether some of your locations will have limited access to stable internet connections. In the case of, say, remote areas in villages or deserts, only good local hardware will do. AI brings unique hardware requirements to restaurant servers, specifically the need for a good GPU chip. This is rare in traditional restaurant configurations. That means you will likely need to upgrade all your servers.

Maintaining and repairing network connections is cheaper and simpler. But replacing a server is not just a physical act. It requires reconfiguring the operating system, installing all software components that connect to other devices (cash registers, monitors, kiosks, etc.), reconfiguring the network, and setting up storage.

To add to this complexity, many activities vital to network function won’t work immediately. They will require multiple iterations of testing and tuning. It’s also likely that the server will contain components from different suppliers, meaning one vendor won’t know all the nuances and will have to consult the technical team of another vendor, which may not be readily available. And if that’s not enough, each restaurant location may have different hardware configurations, so you won’t be able to reconfigure all locations using the same template.

With all that said, maintaining local hardware requires specific attention and expertise. And you must have patience and preparation for long delays before migration can be successfully completed.

Taking a hybrid approach with local hardware and cloud solutions

If you want the highest level of reliability, investing in both local and cloud solutions makes the most sense. For example, your restaurant may primarily rely on an internet connection for cloud connectivity, but if something goes wrong, you have business continuity by falling back on local equipment.

Key stakeholders for infrastructure needs in AI adoption

When assessing what makes the most sense for your business, you will want to involve key stakeholders like the restaurant’s system administrator and the AI technology provider’s technical director. The system administrator can answer questions about the current infrastructure, and the technical director can provide the requirements for the new technology.

Taking a phased delivery approach

Taking a phased approach to selecting and implementing new infrastructure is almost always justified, especially if it’s critical for the business to continue operating uninterrupted. Again, this may seem obvious, but few consider the accompanying complexities. At a minimum, the phased approach implies creating a special orchestrator, both as an additional and temporary software component and as a process. Your software must be able to operate in two modes: without AI technology and with AI technology. It should have the capability to switch seamlessly between both. At most, you need to implement a specialized monitoring and control process, staffed by people with additional responsibilities.

While the phased approach is more expensive and complicated, it is far less risky. Because ultimately your business will need to operate without interruption.

Prioritize the right solutions for your AI goals

Here are some key considerations for upgrading and implementing infrastructure upgrades for AI adoption:

1. Prioritize investing in good internet connectivity and cloud solutions.

2. If ensuring a stable internet connection is difficult, be prepared for significant challenges in upgrading local hardware or consider abandoning AI deployment in those locations altogether.

3. Always use the phased delivery approach and be prepared that delivery won’t happen quickly at all locations.

4. Prioritize systems and approaches that support precision and accuracy as well as reliable performance and speed as it applies to the specific AI technologies you plan to introduce.

Maximizing the effectiveness of service delivery for an offshore software development partner means orchestrating many moving parts. From ensuring smooth proposal development for clients, hiring the right candidates, to balancing expertise across different industries and domain areas, the demand for excellence is essential.

So what does it really take to ensure successful delivery of software development services for external clients? How does a leading firm partner with companies large and small to execute on vital projects?

In this interview, Maksym Riumin, Head of Delivery Practices at Dev.Pro, talks about best practices he uses to make sure that the right talent is in place, and the teams have what they need to help clients succeed in their projects.

What strategies does your team use to ensure high-quality project outcomes?

Maksym: Our Delivery Practice team brings together leaders from various fields like software engineering, project management, quality assurance, development operations, and business analysis. Our main job is to gather and preserve the company’s expertise. Projects vary in length and complexity, with some accumulating more specialized knowledge over time. We collect, keep, and share this expertise across projects.

Our strategy focuses on gathering and sharing knowledge, identifying top experts, and finding effective ways to pass on this expertise to others within the company.

What are the key metrics and practices for maintaining project excellence?

Maksym: Project assessment is crucial. We regularly conduct PM assessments and are currently preparing templates and training technical specialists to do similar assessments in other areas. After the audit, trained technical experts can advise on the project’s development strategy, highlight gaps, assess their criticality, and help communicate this information to the client, explaining the benefits of suggested improvements.

Key KPIs include the number of audits conducted and project health check status. Green means everything is good, yellow requires attention, and red signals potential business risks. We also track more detailed metrics, such as the number of issues resolved and post-audit improvements made.

By comparing results from subsequent audits conducted for the same project and area, we can see if any progress has been made. If issues decrease, it means we are doing everything right. If their number stays the same, we review and adjust our approach.

Some teams struggle with maintaining expertise. What are the most effective ways to transfer expertise within teams where the process is either poorly developed or non-existent?

Maksym: This problem has to be addressed on multiple levels. The best-case scenario and a “win-win-win” situation is when contractors discover personal growth opportunities through mentorship, project processes improve, and clients see clear benefits. So, everyone gains something from this: the contractor, the manager, and the client.

We have many examples of this working well. Our Delivery Practice team offers its expertise to managers and contractors, explaining how we can help. We usually start with a thorough project assessment to understand the context and then deliver a detailed plan.

Recently, we did this for Heartland. We presented our strategy to the client, who saw its value and agreed to implement it. This way, everyone benefits — the client is happy, the project improves, and the team gains valuable experience. We also often involve the specialist who did the initial technical assessment to support the project during implementation. This hands-on approach lets us see results firsthand and verify the effectiveness of our actions.

What are the best practices and approaches to nurturing and developing talent within the company?

Maksym: We identify several development paths for our people. Our Delivery Practice team collaborates closely with HR, Career Development, and Dev.Pro University. Ideally, individuals should be self-motivated. We work with both managers and contractors to show them which different growth opportunities exist. If motivated, they can continue to grow within their project, guided by a technical expert who identifies areas for additional contribution that benefit both the project and the contractor. If that is not possible, Dev.Pro University can offer development in areas unrelated to the project, like soft skills, hard skills, leadership, and more.

The company also has several active communities (e.g., the interview community, the technical expert community, and the pre-sales expert community). If someone wants to grow but can’t do so within their current project, we can be flexible in meeting their needs.

How does Dev.Pro’s interview community help to hire the best talent?

Maksym: We started building this community when I first joined the company. The goal was to establish standardized processes and rules for selecting the best candidates. As the company grew, others expressed interest in joining, so we combined our efforts.

When the job market was highly competitive, we had to fight for candidates. We aimed to attract the right talent who shared our values and were interested in long-term collaboration, while also ensuring a positive interview experience for everyone, even those who didn’t ultimately fit Dev.Pro’s requirements.

We developed common approaches and practices, documented them, and trained our people, explaining the benefits. As a result, about 30% of our contractors are involved in or contribute to the interview community. What’s more, this approach has been successful globally. As Dev.Pro expanded beyond Ukraine, these practices have proven invaluable and universally effective across different markets.

What is the difference between Dev.Pro’s interview community and the standard interview process that other companies employ?

Maksym: It all comes down to motivation. Our interview community is like an exclusive club of people who genuinely enjoy what they do. We do not just invite technical experts to evaluate someone’s skills during the interview. Our tech experts are there from the beginning — starting with the position opening or even the initial kickoff call with the client, where we clarify what the role involves and what kind of candidate we need.

During these kickoff calls, our technical experts determine the candidate’s required level of expertise, understand the scope of the candidate’s future tasks, and learn more about the project and processes. This helps us create the ideal candidate profile and adjust our hiring efforts accordingly. So, Dev.Pro’s interview community is a dedicated group of motivated people who love what they do and get a kick out of sharing their knowledge and continually improving their skills. They aim to leave a positive impression on candidates with their professional approach and minimize the stress associated with job interviews.

Should small companies consider adopting this approach, or should they start with something simpler and scale up as they grow?

Maksym: It makes the most sense for smaller companies. Here is why:

• Any mistakes made during the hiring process tend to have a bigger impact on smaller companies. For example, if a company with only 35 employees hires someone with the wrong soft skills, it can negatively affect the overall team atmosphere.
• Smaller companies can more easily build a close-knit community of motivated individuals who focus on quality and regularly participate in knowledge-sharing meetings to analyze case studies, discuss successes and failures, and explore avenues for improvement. In larger companies, this sense of community is harder to achieve. They may have dedicated groups of technical experts with clear processes for training, selection, testing, feedback, and motivation, but the feeling of belonging to a community is often missing.

We are currently just the right size for this — neither too small nor too large. We have a great base for developing such a community and gradually transitioning to a more scalable and structured model as we grow.

Which strategies do you use for attracting and hiring top-tier talent in the software development industry?

Maksym: First, we create a detailed profile of the ideal candidate, considering their hard and soft skills before we start hiring. We know projects and people vary, so we strive to find the perfect match. That is why we always consult with our clients to learn as much as possible about the position and understand the candidate’s tasks, both initial ones and those further down the line. We consider all these factors because they influence long-term cooperation, which is our main goal.

Secondly, we conduct experience interviews. At Dev.Pro, we focus less on the individual’s academic knowledge and more on their problem-solving skills. For example, when we give candidates a take-home assignment, we are interested in how well they can discuss it with our tech expert during the interview and how efficiently they can explain their thought process, collaborate, ask and answer questions, and incorporate feedback. We care about how they work with others because that is how work gets done in real life.

In simpler terms, we are less concerned about whether the candidate knows textbook definitions of OOP principles. Instead, we want to be sure they can apply these principles in practice. We train our experts to evaluate this using the STAR method (Situation, Task, Action, Result) to discuss past experiences and ask additional questions for deeper insights.

This approach has been useful during our global expansion. In Latin American countries, it is easy to overlook great candidates if we focus solely on academic knowledge. That’s because many of them are unfamiliar with the terms we use in Ukraine. However, this does not mean they lack the required skills or experience.

Many leading companies today use this proven and effective approach, but it is not without challenges. Teaching people to conduct experience interviews is not always straightforward. New experts in our community sometimes struggle to shift from the traditional academic approaches to this practical, experience-based method. In this case, we get our Career Development department involved to rely on the experience of our most seasoned interviewers.

Is the experience interview a simulation of actual work and collaboration on a real project?

Maksym: It is. Before the interview, we send a brief agenda to the candidate explaining the process without listing specific questions. This helps reduce the stress and lets the candidate know what to expect. It makes it easier for them to talk about their experience during the interview without worrying about recalling specific textbook answers.

We can see that this method is effective when candidates who had a great recruitment experience at our company gladly agree to join our interview community and learn how to do it themselves. There is no better feedback.

What is the role of pre-sales in driving business growth?

Maksym: The pre-sales team acts as a bridge between the sales and delivery teams. When sales bring in a potential client, our pre-sales specialists take over. They analyze the client’s needs, determine if our company has the right expertise, and figure out the best approach for the project.

Pre-sales tasks can vary, from organizing technical calls with our experts to drafting proposals that best suit the prospect’s needs and clearly outline our project execution plan.

Our cooperation with pre-sales involves helping them identify the right experts. We can cover a broad range of needs, including finding suitable expertise in project management, software engineering, or quality assurance. We can connect them with top knowledge carriers within certain domains like the restaurant business or fintech. Or we can help locate specialists trained in specific technologies. Some clients might even request details on the number of specialists we have and the scale of their past projects. Our job is to quickly find the most suitable people for each task.

We also recognize that people have different strengths. Some excel at demonstrating their expertise in meetings, and others are better at providing valuable content for pre-sales activities. When the pre-sales team has a request, they come to the Delivery Practice team with details about the client and their needs. We then find the right people and form a team.

While it may not seem too difficult, there are challenges. One of the biggest is that technical contractors might have no experience in pre-sales, which is a unique and highly specialized area of business development. Not every technical person has the corresponding skills, so we must prepare them before involving them in a meeting or other pre-sales activities.

For us, pre-sales is a distinct area where we build a community of talented specialists. We onboard and train them, evaluating their client-facing and pre-sales skills. We analyze who excels in meetings, who can effectively present our expertise, who is strong in creating pre-sales content, and who has the right skills to pitch our company.

These are our tasks when it comes to working with pre-sales. While the Delivery Practice team handles many collaborations, this is the most crucial one because it is key to business development and company growth.

What are the most effective collaboration techniques between the Delivery Practice and pre-sales teams?

Maksym: One primary technique is ensuring everyone understands their role and feels comfortable in it. Technical contractors are used to being given a task and trusted to find the best way to handle it. In pre-sales, they must take a more proactive approach — they do not just wait for instructions from the client; they need to tell the client how things should be done. To help with this shift in communication, we train our contractors to present solutions confidently and guide clients effectively.

Another common scenario is when an expert with extensive knowledge is asked to create a proposal summarizing their expertise on one page. They often struggle because they do not have the sales skills to tell what will grab the client’s attention. In these cases, the pre-sales team helps refine the content. Once these technical experts are trained, it is easier for them to focus on what is most important.

In summary, what is your process for ensuring successful service delivery for clients?

Maksym: The Sales team finds the client, and the Pre-sales team works with them to identify their needs. If necessary, they involve the Delivery Practice team and other specialists. For example, we involve business analysts if we need strategy or estimates. For designing the project architecture, we bring in architects. If there is a specific area of interest, like test automation or performance testing, we find the right experts for that, too. This team can even help kick off the project (e.g., create a Proof of Concept). It all depends on how the collaboration develops.

At Dev.Pro, delivery leaders like Maksym play a pivotal role in ensuring our clients achieve project success, coordinating across teams and making sure the right teams are there to execute. To learn more about how Dev.Pro’s IT experts can transform your project management approach, reach out to us today.

In this interview, Polina Popadenko, a Technical Program Manager with Dev.Pro, shares her first-hand insights into how AI is transforming the retail, restaurant, and hospitality industries. In a conversation with Dev.Pro’s Marketing Project Manager, Daryna Kutova, and Content Lead, Diana Papirovnik, she explains the importance of fostering cohesion and efficiency in IT teams, no matter the industry.

About Polina: Polina began her journey in IT working on mobile app development before moving on to overseeing reporting teams and mobile ordering solutions. Over seven years, she’s built up a comprehensive understanding of how IT teams function in the retail, hospitality, and restaurant industries.

Are there basic elements of good project management that apply to all industries?

Polina: No matter the industry, some things are always the same, like the need to set clear goals for the team. There are plenty of tools you can use: key value results, sprint goals, etc. Any format you agree upon with your team — anything that works for all of you — will do. The important thing is that these goals are well-defined with deadlines, giving everyone a clear understanding of when something needs to be accomplished.

Another crucial point is that everyone, including clients, stakeholders, and developers, must want to achieve these goals. When you’re overwhelmed by work, it’s sometimes easy to forget that. But the fact remains: everyone on the team wants to be successful.

A project manager must clearly understand the current situation, always stay focused on the ultimate goal, and be able to find ways to help the team succeed in reaching these objectives with the time and resources they have available. They must rise above the day-to-day chaos to see the big picture.

If you can take this bird’s eye view, keeping in mind that everyone wants the same thing, you can focus on finding and fixing those gaps, misunderstandings, and issues effectively. That’s why flexibility is such an important and strategic skill for a program manager.

How do you keep up-to-date with evolving trends and tech innovations?

Polina: I find attending conferences to be particularly helpful. They’re good opportunities to pick up on something useful to apply within your current industry. I always bring back many fascinating ideas from these events.

While not everything at these conferences may seem immediately productive, attending can still be worthwhile. Even if only a few speakers resonate with you, their insights can be valuable. It’s a great way to meet new people and exchange experiences with those outside your company, which can give you a fresh perspective on things.

Participating in industry-specific conferences, like Food On Demand, is particularly invaluable. They help you understand the challenges encountered by people working within your industry and those running businesses. It gives you more KYC (Know Your Customer) insights, which you can later implement and use when working on your projects.

Other common conference topics are issues like cost-effectiveness, availability, and stability, which are all interesting to listen and learn about.

For example, at this year’s NRA event (National Restaurant Association Show), various companies involved in the food service and lodging industries gathered to showcase their offerings. It was interesting for me to check out new Point of Sale (POS) solutions introduced by our client’s competitors, looking at their latest features and innovations. At this event, I saw a lot of waiter robots designed to meet the needs of the restaurant business. It turns out that these systems are not deeply integrated with POS and can function almost independently.

By attending that show, I discovered that waiter and cleaner robots are one of the hottest trends in my industry. Now that I can see the demand, I know there’s a genuine interest and it’s obvious that these innovations might be worth exploring further.

However, remember that the goal is not to implement everything you hear about, but to test new ideas and see how they work for you.

How do you see the retail, restaurant, and hospitality industries evolving in the near future?

Polina: There’s a lot of talk about AI now; how to best apply it and how it’s likely to change the world. It’s a fact that AI is present in many solutions already, and its adoption keeps growing. AI today can be used for anything — from tracking third-party delivery issues where AI helps analyze large datasets to identify problems, to handling various smaller tasks.

Chatbots are another popular trend, not just the ones built on ChatGPT, but all sorts of other bots used for customer support to reduce the need for human operators. Then there’s voice ordering — another major trend. It’s a mix of technologies, but the key one uses AI to recognize your voice, understand what you want to order, and help process the order through POS systems.

Automation is also huge right now. The more, the better. Ideally, business owners want to see just two buttons: a “problem” button that identifies and analyzes issues and a “solution” button that fixes them automatically. That’s a joke, of course, but seriously, a lot is being done to automate problem-detection and problem-solving tasks, and we can see substantial progress in that direction.

Another trend I’ve spotted is that restaurant businesses are trying to move away from the current model, where workers are focused on performing just one specific task, whether that’s serving food or taking orders. With all these robots and kiosks handling repetitive tasks, the idea is for staff members to concentrate on ensuring a great customer experience rather than providing a single service. There is a clear shift toward hospitality here.

Is all this AI implementation a good thing for businesses in retail, restaurant, and hospitality?

Polina: I believe it is. Although businesses today both want and fear AI, particularly smaller ones. They like the idea but are intimidated by it at the same time. Still, no one rejects AI, so it’s safe to assume that it benefits businesses in many ways.

I think AI will be widely popular. Businesses across various sectors are looking into this technology with ever-growing curiosity. Naturally, concerns exist about its security and the possibility of AI taking over essential aspects. What can I say? We’ll have to wait and see. For now, as long as it makes life easier, people will keep using it.

In any industry, what’s the secret to keeping teams working well together?

Polina: It all comes down to clear communication — one of Dev.Pro’s core values. Naturally, each team is focused on its own set of tasks and has its own goals and metrics for success within specific time frames, which may not always align.

However, it gets easier when these teams are all part of the same account. In that case, each group shares the same overall goals and tasks.

Of course, you must clearly communicate these overall goals and tasks top-down to ensure everyone is on the same page regarding priorities. When teams depend on each other, cross-team communication becomes paramount. Don’t get me wrong, you need to have a set of tools and processes to ensure your dependencies are documented and visible, and you can track progress, potential risks, and issues. What I wanted to highlight here is: don’t forget about communication. You need to cultivate it in your teams and yourself because many problems can be avoided simply by having proper communication processes in place.

At Dev.Pro, project managers like Polina play a pivotal role in bringing new innovations to our clients that help drive ultimate project success, guiding clear communication across teams and encouraging enthusiastic teamwork. To learn more about how Dev.Pro’s IT experts can transform your project management approach, reach out to us today.

It seems like Artificial Intelligence is everywhere these days, from your internet searches to your refrigerator settings. Across every industry, businesses are keen to find opportunities to transform their operations with AI solutions.

But not all AI implementations go off without a hitch — successfully integrating these powerful tools requires careful research.

In this interview, Daryna Kutova speaks with Yurii Buchchenko, Head of AI Practice at Dev.Pro, about how AI is impacting operations across industries, the differences between traditional and generative AI, and how to successfully integrate these models into your business.

How is AI transforming business operations?

Yurii: Broadly speaking, AI is revolutionizing business operations by optimizing processes and enhancing decision-making. When businesses get it right, the ROI can be truly incredible.

Traditional AI, for example, offers a level of precision and efficiency that manual processes just can’t match, like quickly detecting tumors from raw diagnostic data.

On the other hand, generative AI is making waves in customer engagement and content generation, improving business operations that require versatile task management and creativity.

What are the specific differences between traditional and generative AI?

Yurii: Traditional AI is taught to do one thing on a deep, specialized level, while generative AI is more of a jack-of-all-trades. Generative AI can — theoretically — do anything, including the same tasks as traditional AI, though at the cost of reliability, scalability, and efficiency.

Again, one good example of using traditional AI would be cancer diagnostics. Traditional AI can use its extremely deep understanding to help doctors determine the presence of a tumor and its malignancy with unprecedented accuracy and precision, saving up to 80% of manual work time.

Generative AI, on the other hand, can identify items within images, draw pictures, and comprehend and generate audio. It’s reshaping tasks like customer personalization, providing businesses with the tools to engage customers more effectively by automatically tailoring their experiences based on their customer data.

A significant distinction to keep in mind about generative AI models is their size, however. Large Language Models (LLMs), like ChatGPT, are much larger than traditional AI models, making them more costly and challenging to manage if hosted privately.

How can businesses successfully implement AI into their workflows?

Yurii: The key to successful AI deployment lies in the alignment of AI capabilities with your business goals. You need to make sure that you have high quality, available data, and that you have the right technical expertise to manage the AI lifecycle from development to deployment.

Overall, integrating traditional AI is more complicated and time-consuming compared to generative AI. For traditional AI, gathering and consolidating data from various platforms into one usable format is a significant challenge. However, it might be the best option for your business if you have highly specialized tasks.

Generative AI, particularly pre-trained models, simplify the process and are better suited to creative tasks, but still require expertise in prompt engineering for effective use. Generative AI is also significantly more expensive than traditional models, making them more difficult to scale.

Another key point to consider is whether or not you should self-host the AI models or subscribe to third-party services. While self-hosting offers enhanced privacy and control, it demands significant resources and expertise. Third-party services provide convenience but raise concerns about data security and dependency. Balancing these factors requires understanding of business needs, risk tolerance, and company’s long-term goals.

Can AI really give businesses competitive advantages in saturated markets?

Yurii: AI can give businesses a bigger or smaller competitive edge depending on the type of AI model they implement and whether it’s suited to the tasks they require.

Many companies have data analytics platforms as a backhouse solution, providing data dashboards for human analysis — the core competitive advantage of AI is its ability to automate the decision processes based on that data. AI analyzes that data and recommends actions much faster than a human can.

Businesses operating in the retail, finance, logistics, and marketing fields can use traditional, domain-specific AI models to get ahead with predictive analytics to forecast market fluctuations and real-time insights of in-house data.

At the same time, businesses in sectors like customer service and support, e-commerce, online banking, travel & hospitality, and education are increasingly adopting generative AI to reduce labor costs with conversational AI-like chatbots.

How does the approach to AI implementation vary by industry?

Yurii: The approach depends on the nature of the business and the tasks you aim to solve with AI. Effective strategies involve carefully selecting the AI model and then tailoring the implementation process.

For industries that need AI for simple tasks, generative AI models, such as Large Language Models (LLMs), often come pre-trained, reducing the complexity of implementation. This can be a good option for customer service and support chatbots, where some creativity is required.

For more complex tasks, traditional AI is a better bet, though it requires that businesses gather and prepare vast amounts of data for training their models, demanding specialized expertise and thorough data management. Traditional AI is used in industries like healthcare, where creativity isn’t the goal; traditional AI’s ability to analyze huge amounts of data quickly and accurately is transforming diagnostics and treatment strategies, significantly improving patient outcomes.

Both types of AI provide capabilities inaccessible (or hardly accessible) to regular software products.

Have you ever seen AI implementation fail? Why did it happen?

Yurii: I’ve heard of many cases where businesses had to abandon their plans for AI integration because they hadn’t thought it through.

This happened to companies that wanted to host their own ChatGPT-like generative AI on private infrastructure, but didn’t have enough resources to do so. Similarly, I know of companies that wanted to train their own AI models using proprietary datasets, but lacked a well-defined and realistic data management strategy to fall back on.

How can businesses avoid making those mistakes?

Yurii: There are some important questions to ask yourself before diving into AI implementation. Do I want to go for a pre-trained model or train my own? Is there going to be enough data to feed into the model? Do I have sufficient resources to host my model privately, or should I do it on public infrastructure? Is there necessary AI expertise available within the company to realize this initiative? And so on.

When it comes to AI solutions, there’s no one-size-fits-all approach. A customized AI strategy is necessary to account for the specific needs, resources, and limitations of your business. This involves conducting a thorough analysis to determine the suitability and potential challenges of implementing AI solutions.

To learn more about how AI can transform your business operations, help you scale, and improve ROI, reach out to one of our Dev.Pro experts today.

In order to understand the topic, let’s start by reverse-engineering the success of Cisco, the global leader in SCM [Supply Chain Management].

John Kern, Cisco’s senior VP for supply chain operations mentioned some of the company’s success factors for its digital transformation strategy. Here’s a summary:

1. Agility and resilience are not cheap and worth investing in.
2. Focus on creating a dynamic distributed supply chain: consider dual sourcing, minimize risks by investing in diverse geographic regions, and create strategic partnerships with suppliers.
3. Strive for a greener supply chain always: cut company-generated greenhouse emissions, reduce foam in packaging, and implement circular design principles.
4. SCM starts at the planning stage and belongs there — it precedes R&D, it doesn’t come afterward.

“We’re very aggressive in shifting to a more digital supply chain, leveraging cloud technology, artificial intelligence, machine learning and IoT. And harnessing the value and embedding those technologies into many, many practices.

John Kern, Cisco senior VP supply chain

Inspired yet? Let’s delve into the key questions related to digital transformation in the supply chain.

What is Digital Transformation in Supply Chain Management?

Before diving into the definition of supply chain management digital transformation, let’s first define what SCM is about.

What is Supply Chain Management?

Supply Chain Management is a multi-faceted system of centralized activities, methods, and tools that enable the flow of the goods from raw materials to fulfillment of finished products to the end consumer’s door. This ecosystem includes planning, sourcing, manufacturing, delivery, and return handling.

Defining Digital Transformation in Supply Chain Management

Digital Transformation of the SCM is a complex set of activities that help simplify, automate, and systemize all functions of the supply chain with the aid of technology. It involves website and application development, social media, telephony, chat, SMS, email marketing, and IVR [Interactive Voice Response] technology. System integration is vital for successful DT, — it interconnects business processes and helps integrate a company’s website, ERP, CRM, WMS, IMS, sales, and logistics software into one system for better visibility, control, and decision making.

As we approach a blueprint for how to start Digital Transformation in Supply Chain Management, this final diagnostic chapter reveals the pains and restrictions the industry faces post-pandemic, which DT can help alleviate.

Why are Changes Needed in the Supply Chain Sector?

The pandemic precipitated digital transformations for dozens of industries. Logistics and supply chains are undergoing a major evolution too.

Resilience and Business Continuity over Price Efficiency

The pandemic’s onset highlighted one major weakness in the supply chain: cost efficiency comes at a price. Before the pandemic, all links in the supply chain had targeted a reduction in price, often at the expense of a loss of resiliency and business continuity.

But nearly overnight, price was no longer an issue. The price of a 40-foot container went from $2,000 to $25,000 in two years of pandemic.

Such a shift in the supply-demand paradigm made companies rethink their approach to competition. They needed to regroup and find the balance between cost, speed of delivery and guarantees.

Consumer Expectations of One-Day or Same-Day Delivery

Consumers expect things to be available with a click. Amazon invested $800 million in just one quarter of 2019 to shorten the default Prime delivery term from 2 days to 1 day.

Spencer Fung, CEO of supply chain manager Li & Fung, echoed the significance of speed at a National Retail Federation conference. This is how he replied to high-end brands facing the same pressure to speed up and digitize as a mass merchants:

“We see a world where everything eventually will be digitized and when you digitize processes and businesses, velocity actually increases. So if you don’t digitize parts of your business, you will forever be in the low velocity world. And in a world where consumers are speeding up and they are changing preferences on a minute-by-minute basis, even the luxury brands will have to invest.

Spencer Fung, CEO of Li & Fung

Risk Management and Tier 2 and 3 Visibility

According to a Vuealta study, 30% of companies were subject to disruptions due to the failure of a single supplier. Geopolitical issues, natural disasters, reputation management, and visibility of tier 2 suppliers are all subject to risk management activities in the supply industry.

With the proliferation of blockchain technology, IoT, AI, computer vision, and big data, the industry gets more and more tools to proactively address these challenges.

Labor and Safety Issues: Continuous Public Focus

As smartphones become omnipresent, labor and safety concerns rapidly decrease and manufacturing and logistic companies are spurred into action by fear of public disclosure by whistleblowers. For example, companies invest into creating proper working conditions and stop hiring underaged workers in Asia, because of fear of video evidence of unethical conduct in the Western media.

Corporate Social Responsibility has evolved to better control the working conditions of employees. Yet further digital transformation activities and tools are needed to fully eradicate similar labor and safety issues.

Unethical sourcing is another issue of concern in this domain. Top Glove Corp, a rubber glove manufacturer, picked up a hefty bill for using forced labor when its IPO got delayed over a ban issued by the U.S.’s Customs and Border Protection.

There is a huge disconnect between the priorities of the labor and safety of the developing world and developed countries. Safety Management Software and EHS solutions help address these concerns.

Environmental and Social Governance [ESG]

ESG practices are relatively new but they demand a lot of focus from the industry leaders to comply and even mold this new corporate framework and philosophy.

Sustainability, human rights, an environmentally conscious mindset, consumer protection, and employee rights all make use of technology to move forward.

Best Practices for Rolling out Digital Transformation in Supply Chain

These empirical best practices will help implement digital transformation initiatives throughout the organization if you are looking to integrate vendor-made solutions or opt to develop a custom SCM system.

Consult Several Digital Transformation Experts

Before starting to choose a tech partner, reach out to a few software development companies for a consultation.

Even if you have to pay for an audit, review of your status quo and a digital transformation roadmap, you will have ended up with an invaluable set of expert opinions that will save you loads of resources down the road.

Consider Multiple Vendors for Each Service, Look for Visionaries

When choosing a SCM software vendor, make sure to consider at least 3–5 companies and include younger tech solutions, like those who place into Gartner’s Visionary quadrant. They often turn out amazing value-for-money with cutting edge features.

Align Digital Transformation Goals with Business Priorities

Choosing your priorities is vital, as is aligning your technical arsenal to your company-wide goals.

If you are an international logistics company, translating your SaaS solution into major languages is a top priority, as well as ensuring compliance across borders and currencies.

Optimize Cloud Cost in Line with Best FinOps Practices

When developing your supply chain digital transformation strategy, ensure you integrate the cloud cost optimization best practices into the architecture of your systems. With multiple cloud services and subscriptions used for a diverse range of tools within the company, some regular rightsizing and right costing measures can lead to five or six figure savings.

Follow the Demand and Make Data-Driven Decisions

Demand-driven supply chain management is now a reality with predictive analytics, AI, ML, drone inventory-taking, and barcoding tech. Data is capable of providing more answers to optimize the business processes across all stages of the material sourcing, manufacturing, and delivery. Ongoing business process optimization is best incorporated into the monthly meeting schedule.

The below overview of the top SCM suppliers will help you understand the fundamental features and functions of the future ecosystem. For an even deeper understanding of the subject, you may also want to check out our piece on an industry tightly connected with SC: Digital Transformation in Retail: Trends That Can Drive Your Growth

Key Digital Supply Chain Transformation Challenges

The challenges of the industry are legacy-derived as well as post-covid-related.

Legacy and Corporate Culture Resistance to Digitization

There is a lot of on-prem software still in the industry, but cloud technology offers so much agility and ensures minimal downtime and disruptions. Creating a corporate culture that welcomes and embraces technical change is vital.

Inflated Freight Prices: Temporary or the New Norm?

It is not yet clear if the prices will even out as business returns to normal.

Unpredictable Pandemic Effects

It’s unknown how long and severe the next stages of pandemic may be, which incapacitates forecast or order goods and services. This particularly affects those with long production cycles.

Multi-Jurisdiction Operations

Many logistics and delivery companies operate across borders. Complying with ever-changing regulations across different jurisdictions is a resource-draining mission.

Lack of Skills: Path to Team Extension or Managed IT Services?

Servicing digital chain supply logistics transformation requires a lot of technical talent and know-how. Software developers, cloud specialists, blockchain engineers, and DevOps experts are just a few of the tech talent pool needed to customize and integrate multiple software solutions for warehouse, logistics, and order management.

Hiring an outsourced team of software engineers or signing up for managed IT services or getting a team extension for your internal IT department is often a sensible way forward.

Supply Chain Management Software: Status Quo, Leaders, and Features

Custom-made Supply Chain Management Software is currently rare due to the proliferation of cloud technology and affordable SCM SaaS solutions. These are usually integrated with ERP, CRM, S&OP, financial, inventory management software, and other company-adopted SaaS systems.

Supply Chain Management Software Market Stats

According to a Research and Markets report, the Supply Chain Management software market was worth $14.6 billion in 2019, and is predicted to grow to $19 billion at a five-year CAGR of 6.7%.

Out of the $17.3 billion in revenue forecasted for the market in 2021, $8.7 billion was generated in the U.S.

The market is usually subdivided into the following segments:

• Supply Chain Planning Solutions
• Procurement Software
• Transportation Management System
• Warehouse Management System

Supply Chain Planning Software Features

Many of the SCM solution types have transient features, so let’s list those for Supply Chain Planning, as they are likely to be present in other types:

• Supplier management
• Warehouse management
• Transportation management
• Inventory management
• Order fulfillment
• Electronic Data Interchange [EDI]
• Sale & Operations Planning
• Demand Forecasting with Predictive AI Features

Supply Chain Planning Software Major Vendors

Gartner’s Magic Quadrant for Supply Chain Planning Solutions places Blue Yonder, Kinaxis, E2open, Logility, and OMP in leadership roles and positions SAP, Oracle, Dassault Systems, Demand Solutions, and Infor as challengers.

Blue Yonder recently announced the acquisition of Panasonic, which lays the path to a yet another revolutionary spin of this leading technology.

In a speech , the CEO of Blue Yonder, Prakash Seshadri, emphasized four areas of focus for a Panasonic-enabled company:

1. Industrialization of the supply chain;
2. New opportunities to realize the “Power of three” combining Panasonic’s Edge with Cloud technology and AI/ML;
3. Transition of the center of gravity and responsiveness of supply chain from the C-suite to frontlines;
4. Real-time visibility and control as the default setting in the post-pandemic reality.

Benefits of Digital Transformation in Supply Chain Management

Digitizing your SCM may seem overwhelming, but there are rewards to look forward to:

Velocity

Pandemic revealed a major fault of the system focused on the cost effectiveness above all. But velocity proved more valuable in the end. Continuity of business and velocity in crises are also facilitated by new technology that’s embedded into various SCM software systems.

Speed

One of the most obvious advantages of automation is speed of processing. It takes drones about ten times as little time to do stock inventory than it takes humans, for example.

Transparency

From ethical sourcing and transparent pricing to executive bonuses and environmental impacts, supply chains would benefit from more transparent methods, tools and outputs. Digital supply chain transformation offers transparency as it’s core pillar where big data, blockchain, AI, ML serve to make data accessible for all stakeholders. This includes the manufacturers, logistics companies, warehouses, governmental institutions, and the end user.

Accuracy

Human work is prone to errors, so with the rise of IoT, computer vision and barcode scanning technology, warehouse inventory management is getting more precise and accurate.

Cost efficiency

While there are multiple use cases about supply chain digital transformation benefits, one example, given by Jon Chambers at P&G, showed how he helped one of the Lenor-producing plants save six figure amounts in warehouse rental. A simple data visualization with average daily shipment along the horizontal axis and coefficient variation of shipments along the vertical axis helped change the company’s production schedule, significantly reducing costs.

For the sake of the balanced view, let’s also consider key issues on the way to a fully digitized company in the supply chain industry.

How to Prepare Your Supply Chain Digital Transformation Strategy

The depth and breadth of the digital transformation strategy for your organization’s supply chain depends on a myriad of factors. They all include these stages:

1. Full audit of the existing tech stack and online presence [from ERP, CRM, SCM, Cloud Services, to social network presence and digital media review].
2. Understanding business goals in the short term and long term, and defining resources available [financial min-max amounts, talent pool, and deadlines].
3. Finding how digital transformation can help bridge the gap between status quo and the goals while prioritizing the methods with quickest ROI.
4. Elaborating a step-by-step roadmap with people responsible, deadlines and resources allocated to each activity.
5. Implementing the roadmap internally or by hiring an outsourced digital transformation company.

DevPro’s team offers hands-on expertise in building digitally-savvy software products from scratch as well as helping drive digital transformation for forward-looking companies across FinTech, eCommerce, InsureTech, as well as supply chain industries. Fill out this form to schedule a consultation on your next step toward a fully digitized enterprise.

Yep, the cloud is overtaking on-prem deployment:

• Gartner predicts that public cloud services end-user spending will grow to $482 billion by 2022 [an increase of 21.7% from 2021].
• Cloud computing is in its mass adoption stage. According to a survey by O’Reilly, 90% of organizations use it to some extent.
• Nearly a half [47%] of respondents to TKTK’s The Cloud in 2021: Adoption Continues survey say their organizations have a cloud-first approach and consider the cloud environment to be their main priority.

It’s safe to say that cloud development is the new norm. Let’s find out how your company can benefit from the technology, what pitfalls to look out for, and which best practices can help you drive ROI from cloud adoption.

The ABC of Cloud Software Development

What Is Cloud Development?

There exist different definitions of cloud development and we will use its most general interpretation for this article:

Cloud Development is the process of creating software solutions with the help of cloud compute capacity as opposed to on-prem servers. In this broadest context, we include development, deployment, and storage of any type of software products on cloud hosting or with the help of other cloud services, including web applications, mobile applications, databases.

Cloud-native software development is an approach to product development that is characterized by using cloud environments from the earliest stages of the SDLC cycle, from planning, designing, coding, building, to deploying, running, and monitoring. This approach takes advantage of the benefits inherent to cloud technology, including agility, scalability, cost-efficiency, and security. Kubernetes, Docker, APIs, and Kafka tools are often chosen to facilitate a cloud-native development framework.

With theory covered, let’s get down to practice: how do you kick off the cloud-based software development process?

Cloud-Based Development: What to Start With?

Choose the Deployment Model

Three major cloud deployment models are used by organizations, with different levels of security and cost ratios.

• Private [the most expensive of the three types, a private cloud also offers the most secure environment, so it is often used to process and store confidential data]
• Public [the cheapest deployment, it is usually used for non-critical data processing and storage]
• Hybrid [a combination of public and private: it allows you to scale the workload at sensible rates with secured private data]

Depending on the size and maturity of your company, budgets available, and sensitivity of your data, you should choose the optimal deployment model for your case.

Decide on the Service Model

The three service models delineate how much of the workload and responsibility lies on the cloud service provider and how much is left for the client.

IaaS [Infrastructure as a Service] — the cloud service provider offers storage and Virtual Machines only — a basic infrastructure.

PaaS [Platform as a Service] — on top of networking, storage, servers and virtualization included in the IaaS, PaaS also includes extended os, middleware and runtime.

SaaS [Software as a Service] — All of the hardware and software elements are taken care of by a vendor, including the data and application itself.

This decision is based on many factors, and some of these are deduced by answering these questions:

• How much technical talent do you have to config, maintain and monitor hardware and software?
• How much upfront cost are you happy to face or are you on a low-budget, pay-as-you-go mentality?
• Do you have sufficient confidence, market knowledge, and funding to see this project to the end, or is it just an experiment?

Now you are ready for the next big decision: the battle of the titans.

Select a Cloud Service Provider(s)

Amazon Web Services vs Google Cloud Platform vs Azure is a tough but critical decision to take. We recommend getting a sense of FinOps fundamentals before you go down this path.

Consider these factors before arriving at a verdict:

1. Where are you and your clients based? China? Alibaba may be the answer? America? You are spoiled for choice, but some states may get better rates than others depending on your proximity to data centers.
2. What does your competition and industry leaders use? Why? Check the use cases for specific economic segments.
3. Is your workload predictable and how far if so? A year out? Three years out?
4. Do you have Google-certified engineers onboard or Amazon-certified talent?
5. Do you have infrastructure already in use that is supplied by one of the shortlisted providers?

Create or Outsource a Software Development Team

With all executive decisions out of the way, it’s time to decide on the team. professional enough to execute your software development project. If you have enough technical expertise on your existing team, great! If not, your CTO will have to suggest the optimal way of moving forward: hire more talent or outsource the cloud software development project.

Should you want to cut your time-to-market without breaking your budget, this guide on how to select a development vendor will come handy.

Once these major choices are made, it’s time to kick off your SDLC [Software Development Life Cycle].

Cloud Software Development Life Cycle [CSDLC or CDLC]

The cloud Software Development Life Cycle echoes the regular on-site SDLC, albeit with some changes arising from multiple benefits of the microservice architecture and CI/CD, which is characteristic of cloud computing [speed, agility, resilience, scalability].

These are the main phases:

Research and Data Gathering

Business requirements and cloud service suppliers are analyzed.

Decision Making

What service, and deployment model to use, which vendor and tools to choose.

Planning

Team and project planning with plenty deliverables, including development roadmap, config management and QA plan.

Analysis

System components are defined and a front-page architecture draft is considered. The initial process assignment and task distribution between teams takes place.

Design

Granular architecture is created based on requirements and resources available.

Implementation

Coding stage and commencement of testing phase.

Deployment

Deploying and gathering of feedback is a continuous process

Maintenance

Bug fixing and code improvement based on attained comments from end users, testers and developers

Retirement

Some system elements may grow redundant and are retired with consecutive fine-tuning of the remainings components

Ideally such a cloud software development life cycle will be looped as part of the CI/CD process for frequent releases, higer code quality and quicker time-to-market. A plethora of tools can help process from one stage to the next one seamlessly. These are the major tools from the arsenal of cloud engineers and architects.

Cloud Software Development Tools

There are two major alternatives to developing on cloud:

• Cloud-first approach [The less popular approach. It involves creating the cloud platform first and then building tools to run on top of it]
• Tool-first approach to PaaS [The hostable development platform is created first and pushed to the cloud after]

Multiple approaches to system architecture and proliferation of software solutions and platforms for development ensure a wide range of tools is available: cloud services by both major vendors and third parties.

GCP, for example, has CloudCode, Cloud SDK and Spring Framework tools to facilitate the coding process, Cloud Build and Jenkins on Google Cloud is used for building, while Google Cloud Deploy and Cloud Deployment Manager is used for the deployment phase. AWS has the most extensive arsenal of tools and Azure also boasts an ample assortment.

Third-party independent or open-source players also contribute to a cloud engineer’s technology stack. For example, Kubernetes and Docker are indispensable for an army of cloud professionals.

Best Practices for Cloud Software Development

Planning, UI/UX as a Firm Foundation of a Solid Product

Lincoln once said: “If I had six hours to chop down a tree, I would spend four hours sharpening my axe”.

This is true in cloud software development, as poor architecture leads to wasted resources and fixing an error early is way cheaper than correcting it after deployment. Likewise, good UX design is capable of boosting traction and securing the next round of investment.

Vendor Selection: Any System is as Good as its Weakest Link

There are two major vendors a tech company may need to procure to develop a software product in the cloud:

1. Cloud service and tools suppliers
2. Cloud software engineering company

While tool selection is defined by the existing infrastructure, talent, and budgets, an outsourcing partner needs to go through a meticulous selection process. Here’s our tips on how to hire a remote IT team.

DevOps: CI/CD as the Catalizer and Stabilizer

A CI/CD framework is nearly indispensable for a microservices architecture.

Automating testing processes and integrating them as early as possible into the SDLC can ensure a fast, uninterrupted release of new features and makes the entire process more predictable and stable.

Cost Optimization

FinOps culture adoption is becoming the best practice for everything cloud.

A well selected cloud service provider, choice of instance type, and knowledge of other right-sizing and right-costing methods let companies embed their Cloud Cost Optimization strategy into the company’s organizational fabric and tame bills sustainably.

Takeaways

Having a multi-cloud and a multi-vendor cloud infrastructure is more of a norm than an exception in 2022.

Cloud software development is being propelled by market consolidation, mature vendor management instruments, the proliferation of containerization, and growth of open-source technologies. Big Data, AI, IoT, ML also contribute to the exponential surge in the evolution of the cloud.

Whatever stage of cloud adoption your company is at, DevPro has the experience and resources to help you quickly migrate from on-prem to cloud or scale your existing resources to fit your business requirements. Reach out to the sales department to see our cloud tech use cases.

With the onset of mobile food ordering tech, speaking to a live agent over the phone is as distant a reality as dialing a number on a rotary phone.

Instead, we are spoiled by user-friendly apps that have images, prices, discounts, loyalty programs, and convenient filtering by location, price, brand. We can arrange food delivery on the go, pay online, and even track a pizza as it goes into the oven.

No app? No problem, you can use a website ordering system, get an SMS confirmation, track your order on a restaurant site, get your burger with no onions, just as you like it — without ever speaking to a human being.

It all sounds easy from a customer perspective, however it’s a cut-throat business for food operators and delivery services. As the market matures and players like DoorDash and Deliveroo go public during the lows of pandemic, there’s significant consolidation happening with M&A deals [like GrubHub acquisition by Just Eat for $7.3 billion, and Uber Eats acquiring Postmates for $2.65 billion].

Large fast food chains, like McDonalds, Starbucks, Dominos, Dunkin Donuts, Wendy’s are competing with the delivery aggregators by developing and promoting their brands’ automated restaurant ordering systems.

McDonald’s core growth strategy aims to double down on the 3Ds [Delivery, Digital, and Drive Thru]. With its massive scale — 120 countries, 33,000 outlets, and 60 million users — scaling its tech is a top priority. One of the digital transformation cases for this fast food behemoth includes MCdonald’s Hong Kong’s acquisition of 1.8 million digital users in just 4 months, thanks to a highly successful Facebook campaign.

In this article we’ll look at automated ordering systems software development in detail. Read on if you want to know the answers to these questions:

What tech stack is used for these solutions? Which features are must-haves? What’s the algorithm for building an automatic ordering system? What vendor or third-party tools are integrated with each other to make automation seamless?

Online Food Ordering Apps: Investors’ Magnet for Years to Come

The boom in Restaurant Tech is a silver lining to the pandemic cloud for the food and beverage [F&B] industry. Eating out habits changed drastically overnight and food tech has seen an influx of investment, with food ordering and delivery services leading the way.

• US food delivery revenues have been growing steadily, adding 20% between 2019 and 2020 to reach $26.5 billion. User numbers have also increased over the years, from 66 million in 2015 to 111 million in 2020. This means that 1 in 3 people in the US actively use a food delivery app on their smartphone.

• CBInsights found that food ordering and delivery systems are still in their early days and predicted a continuous, vigorous growth over the next 7 years. This reputable think tank expects global revenues to triple from $100 billion in 2020 to $300 billion by 2027.

Even though automated restaurant ordering systems are just now nearing mass adoption, there’s enough user data for the main features to have crystallized as the golden standard for the industry. Let’s consider them.

Must-Have Features for Automated Restaurant Ordering Systems and Apps

The main differences in these types of solutions come from these factors:

1. Proprietary software by a food operator vs. marketplace type delivery [Wendy’s vs JustEat: delivery service logistics, payment, loyalty programs, ranking algorithm, table reservation feature, monetization and commission modules, merchant dashboard etc].
2. Geographical location [USA vs China: different payment systems, currencies, cloud service providers, social media integrations, etc].
3. Quick Service Restaurants vs FSR: [SubWay vs Nando’s: table reservations, loyalty program, delivery, takeout modules]
4. Speciality differentiator [Pizza vs burgers vs sushi: topping module for pizza, DIY customization feature for burgers]

Apart from the differences in the mix and types of technical features for automatic ordering from system to system, the following modules are staples in the industry:

Menu Options in Restaurant Ordering Systems

• Catalog of merchants with respective data fields and images
• Catalog of dishes with predefined information fields and images
• Sorting and filtering options [by cuisine, location, budget, by starter / dessert / main dish, etc.]

Food Ordering Module

• Table service option to reserve a table, note preferences, special occasion, or cancel a table
• Delivery module to manage communication between the merchant, user, and driver
• Takeout alternative to manage takeaways and curbside pickup
• Website integrations and a mobile app
• Integration with notification center to send out automated messages in the predefined channel [WhatsApp, sms etc].

Payment, Commissions and Invoicing

• User payment features will entail a breakdown and calculation of prices for orders food, commission, and fees
• Payment system integration with a set of contracted payment methods [PayPal, Visa and MasterCard, Apple, and Google Pay]
• Order refunds and cancellations
• Merchants and drivers will also have accounting and invoicing features

Reporting and Analytics

[differs depending on the role: merchant, driver, user]

• Merchant: Daily sales, bestsellers. Average check, commissions
• Delivery associate: weekly, daily rides, deliveries, commissions, fees
• Order history, payment details, coupons and discounts applied

Review and Rankings

[this feature can be applicable to food, merchant, driver, user]

• Ability to leave a review and rank a restaurant, as well as driver
• Ability to read reviews and view rankings on multiple touchpoints: merchant catalog, restaurant page, and dish page

Loyalty and Support

• Order stats
• Personalized offers
• FAQ
• Premium subscription details [for example, Eats Pass and DashPass]

Revenue Management Features

• Coupons and personalized discounts
• Peak hours bonus for drivers
• Small order fee management
• Price comparison with other apps to offer the best deals for bargain-sensitive users who shop multiple apps before ordering
• Merchant offers and deals [BOGO, get X% off if you buy Y items, get X% off if you buy in happy hours, and first-time buyer deals]
• Regular customer bonuses
• Weekly / monthly subscriptions plans

Heat Map and Map Modules

• Users can see restaurants on a map
• Drivers can see a heatmap of busy and super busy areas, schedule their shifts and book slots for delivery

Delivery Management

• This feature allows merchant to receive orders per menu and process it
• Order cancellation
• Order pick up and courier management

Chat and Notification Center

• Automated notifications as the order gets processed
• Real-time push notifications for time-limited deals and promos for location-based targeting

QR Code Food Ordering

• QR code use for marketing
• QR code use for contactless ordering and menu reading on-site

Social Media Integration

• Meta integration for Facebook, Messenger, and Instagram ordering and promos
• TikTok integration for promotion and advertising purposes

Third-Party Integration

• Integration with third-party apps, like HRM systems, accounting, and CRMs

IoT Integrations

• Barcode scanners
• RFID
• Camera sensors in kitchens

Read our in depth article on use of IoT for restaurants.

Account Management & Access Management

• User account
• Merchant account
• Driver account
• MFA, role-based authentication for merchants and drivers

Automated ordering systems for restaurants need to have smooth integrations so that all processes and notifications flow smoothly from one stage to another.

Steps to Build Your Automated Restaurant Ordering System

If you task your team with developing a fully automated ordering and delivery app for restaurants, your starting point and business requirements will define the timeline, budgets, and operational constraints.

If you have to build an automatic food ordering systems from scratch, your team will follow these milstone steps:

1. Project discovery phase: Ascertain the scope of work, gather business case requirements as perceived by major stakeholders, scrutinize market, competitors, conduct user interviews, create user avatar, and design a high-level project roadmap.
2. Plan: This is when you take all of the facts and findings of the project discovery stage and make conclusions and plans based on them. A team, milestone actions, budgets, timelines, tools, and resources need to be defined at this stage.
3. Design stage will result in high-level design and architecture as well as a low-level design for system components. The team will have a set of detailed documents to enable the development stage, which includes: System design document; Plans: DR, security, training, conversion, unit & integration test plans, and implementation document;
   Manuals: Maintenance, Sys Admin, and User manuals;
   Requirement traceability Matrix.
4. Development & Testing: When all the tools and team are ready and systems are procured and configured, the code building process begins. Thanks to cloud-native software development, CI/CD processes are usually implemented and automated testing starts as early as possible.
5. Deployment stage results in the code are deployed to the production environment and feedback is gathered from users and developers for continuous improvement.
6. Integration with Third-Party Systems, IoTs may take place at an earlier stage of the SDLC, as automation suggested seamless two-way communication of multiple solutions.
7. Maintenance, Security, Updates are also a continuous endeavor in the modern software development life cycle as new commits, and software releases are frequent. DevSecOps integrates security as part of the continuous deployment practice.

While this is just a high-level overview of how to build a restaurant automation system for food ordering and delivery, some companies prefer to outsource software development to tech partners with experience in the F&B industry.

Where to Begin?

There are many risks for restaurant automation systems at each step of the process: from ideation to maintenance. Whether you have to start building it from scratch or want to modernize your current solution, there are key architectural and vendor decisions to be made that will impact the cost, resilience, and availability of systems for years to come.

Unless you have a strong team with vast experience in large-scale software applications, you may want to consider hiring a software development partner that is well-versed in mobile app development and cloud technologies. Even if you involve these experts for the initial discovery and design stages, the ROI will be enjoyed for years to come.

Dev.Pro’s team has helped a number of clients develop SaaS applications and proprietary software solutions for hospitality and SMB. Some examples include Lavu POS, which features the POS-related background, and Global Payments. These cases demonstrate our portfolio from reporting and payment system integration angles.

Discuss your project with our tech-savvy sales associates to obtain estimates with a timeline and budget for your automated restaurant ordering solution development.

IoT in restaurants is capable of boosting your bottom line by slashing utility bills, reducing waste, increasing staff productivity, and decreasing working hours, as well as nurturing customer loyalty.

In the highly competitive but low-margin business like restaurants, an opportunity to lower costs is always welcomed.

Let’s check out some of the real-life cases of how the Internet of Things is employed to make restaurants a safer, more comfortable environment for guests and workers, and a better money-making machine for stakeholders.

Can IoT Make Restaurants More Efficient?

IoT devices perform a number of functions in the food service industry, from the primitive mission of logging certain physical parameters, including temperature, vibrations, and lighting, to being a part of the predictive maintenance algorithms.

In this capacity they get combined with big data and AI to help predict instances of breakage and prevent massive financial losses.

One such example is shared by Johan Nilssen, Vice President of TetraPak Services, where their IoT devices monitor equipment vibrations for predictive maintenance purposes. As a global player, they ship their packaging assembly lines to Argentina, where it can take up to 96 hours to clear customs. By predicting breakage of equipment using vibration monitoring with IoT sensors, TetraPak is able to ship parts in advance and save hundreds of thousands of tons of milk from going spoilt for over a week.

Peter Cryan of Inspire Brands, who own Baskin-Robbins, Arby’s, and more, says the company uses IoT on their dishwashers. This led them to discover that one unit was performing twice the number of washing cycles a day as the others: 90 vs 45 cycles as average. It turned out that every time a fork would fall on the floor, it got into a dishwasher for a full cycle, wasting tons of water, detergent, and electricity.

FoodTech integrates Internet of Things into both downstream and upstream segments. In this piece, we will focus on the multiple uses of IOT devices for restaurants .

Benefits Of Using IoT For Restaurants

Connected kitchens are a new norm for many big players in the food service industry. Let’s explore some of the uses of IoT in restaurants and cafes.

Order from the Table

There are a few ways an IoT can be used so that customers can order food, call a waiter to the table: a QR code can be used to identify the table and lead a customer to a website or an application with respective choices.

Alternatively, a device with a few buttons can be placed on the table so that visitors can press certain buttons to call for a waiter or request a bill.

Pay from the Table

Ready to Pay is one of several solutions that allow you to check out a menu, order food, pay for it, reward a server with a tip, and leave a review by scanning a QR code.

Moreover, the solution helps restaurants turn tables 34 minutes faster, drive tips by 40% and increase average check by 15%.

ReadyToPay allows to order, pay, tip, and fill out a survey by scanning a QR code

Food Waste Management: Integral Part of Connected Kitchens

Food waste management sounds like a formal insignificant routine until you learn that over 30% of all food grown on the planet is wasted. On the other hand, the human population and its appetite is growing with FAO forecasting the need to feed 10 billion people by 2050 as compared to 7.5 billion in 2022. Moreover, the majority of arable land is already being cultivated and this method of increasing agricultural production has been virtually exhausted by now.

These three facts make waste management one of the most practical and least expensive ways [financially and environmentally] to bridge this widening gap.

Winnow is a leading waste management software solution. It uses smart IoT scales paired with AI and a specially developed software application to weight, control, analyze and reduce food waste in kitchens. They cooperate with global hospitality behemoths like Hilton, Accor, and Marriott.

To illustrate the scale of potential savings, Restaurant Associates saved 15 tons of food waste, cutting it in half in 11 pilot sites, avoiding 50 tons of CO2 annually.

Boosting Average Check

Gamification is one of the big trends of restaurant tech trends in 2022 and IoT devices are capable of boosting loyalty and driving brand recognition, as well as increasing the average check.

Kodisoft offers a number of IoT devices for the restaurant industry, including an interactive table that works as a gaming board, menu, order and payment placement tool. They managed to drive average check by 32% as a result of integrating this IoT technology into the ordering process.

Kodisoft revolutionizes the restaurant industry with Azure IoT Hub

Loss Prevention in Restaurants

Monnit offers a number of IoT devices for commercial fridges, including motion detection sensors and open / close monitoring ones. They can help management monitor when the fridge door is open or closed and if there is motion in the fridge via restricted-access dashboard, reinforcing loss prevention.

Other IoT applications produced for commercial fridges include temperature monitoring, water detection, AC current measuring, and vibration monitoring.

Training Team to Drive Food Quality and Consistency

Another idea that is IoT-based and designed to help back of house restaurant staff learn faster and produce high-quality products is Panasonic’s Kronosys glasses.

The technology is being developed to help new chefs in the kitchen master recipes quicker and present them in a consistent manner time after time again. The gadget combines several technologies that include multilingual performance and voice recognition. In the era of staff shortages and quick change of culinary trends, such devices can help more efficient ways to develop a new menu, roll it out across a chain of outlets and control consistency of execution with time.

Complying with Food Safety Regulations

The U.S.’s Health and Safety regulations are extremely stringent, as public safety is an utmost priority, especially in the times of pandemic.

Keeping your fridges compliant with the health and public safety regulations is not only good for your reputation, but can also help prevent fines and restaurant closures.

Digital 6 labs helps food operators lower food safety liability by providing pre-configured self-contained waterproof air-gapped temperature sensors for industrial fridges.

IOT Devices in Restaurant Management: Lowering Utility Bills

Lowering utility bills was one of the main goals of Inspire when they started using IoT in restaurants.

Inspire, the fourth-largest restaurant company in the U.S., put this change into action by using a central HVAC monitoring and control system. Not only can Inspire’s staff monitor how the AC is being used, but they can also control it centrally, ensuring that factors like personal preference and team turnover do not affect the cost of air conditioning.

The company’s district outlier reports with electricity usage also help to discipline, coach, and raise accountability for this cost center.

Decreasing Workload for Teams in Connected Restaurants

Another example of how IoT benefits restaurants comes from Peter Cryan’s speech. Chefs must note the temperature of beef sheets 40–50 times a day to stay compliant. IoT devices freed up their hands so they can prioritize other less routine tasks.

Raising Food Quality

Cost saving occurs on multiple levels in restaurants that use IoT devices to monitor and report on the processes from warehouse to kitchens.

Tellit helped Restaurant Technologies [RT] improve their cooking oil management process across 25,000 food service locations. The IoT devices help elevate the filtering technology that has a direct impact on both: oil life and food quality. Further out, outlets get to know comparative statistics if they use too much of the cooking oil compared to other eateries and if they are in compliance with pertinent national regulations and internal standards.

Predictive Maintenance & Remote Controls

A number of IoT devices can help monitor kitchen equipment for breakages or signs of malfunctioning: Temperature sensors and water sensors will help recognize issues like leakage at an early stage.

Vibration sensors can also be used to diagnose issues and serve as tokens of natural wear-and-tear, that may prompt a timely purchasing of a worn out part and prevent a breakage altogether.

Remote control is another feature that saves thousands of dollars at a time.

Spotting Issues in Chain Restaurants with IoT Devices

In a chain operation, the success of one restaurant cannot be precisely replicated by other franchises, but the lessons learned from one outlet can be applied to others.

Having a comparative table of metrics and data for hundreds of units in a chain restaurant can help diagnose issues quickly, single them out, address them locally and then ensure they are not repeated chain-wide. This is similar to the example from the first chapter about a dishwasher used for every fork that is accidentally dropped on the floor.

How Restaurants Can Implement the Internet of Things

With all of the above examples of how the Internet of Things helps restaurants prosper, save on utility bills, and drive customer engagement, many companies turn to the best practices of IoT integrations.

There are a few steps to be taken for an efficient IoT strategy implementation in F&B segment:

1. Conduct preliminary assessments with a few IoT solution providers as well as system integration companies to understand their options in terms of ROI expected from specific equipment and its installation.
2. Align your company goals, budget, and potential benefits with the offers and decide on the vendor for both: developers of devices and the system integrator. [Cloud service providers are also a critical part of this technical puzzle, so make sure you use a qualified cloud solution engineer to select the right services and negotiate your terms.]
3. Assign a responsible person in your company, draft a roadmap with the chosen vendors and get to implementation as soon as approved by stakeholders.

It’s crucial to choose software integration vendors with a background in the restaurant industry and ample experience with cloud architecture, as IoT devices have their own limitations, like security vulnerabilities.

The Future of IoT for Restaurants

There’s no doubt that the future of the Internet of Things in the food service industry is bright, as bigger companies will use it as a competitive advantage sooner rather than later, making it a norm in the industry.

Many solutions, like fridge sensors, are far from expensive and offer a quick ROI. It’s not too far-fetched to assume that sooner rather than later IoTaaS will be as widespread as SaaS and IaaS are now. This means that one supplier could ensure a fully connected kitchen at a monthly subscription.
Until then, DevPro’s system integration experts will gladly extend our ample food and beverage experience to help you roll out an IoT strategy to drive your bottom line according to your company’s business goals. Schedule your one-on-one meeting with our veteran sales manager today.

“Summing up the state of the play in Restaurant Tech Market in late 2021, it’s safe to say this is a case of every cloud having a silver lining. While the F&B industry took a major blow in 2020, their tech satellite domain saw a massive injection of investment, interest, and innovation. This will shape the food service domain for decades ahead.”

Andrew Ilyin, Delivery Director, Dev.Pro

This Restaurant Tech white paper is a deep dive into the state of things in the food service industry after the pandemic.

On the darker side of this story, Full Service Restaurants in the USA lost 30% in revenue in 2020, according to the US National Restaurant Association. Over 100,000 establishments [17%] closed for good during the pandemic.

On the brighter end of the spectrum, investors rushed to invest in restaurant technologies that allowed the food service industry to produce and serve more food: safer, faster, sustainably, and with fewer human resources. According to AgFunder, in the first half of the 2020, FoodTech attracted nearly $15 billion [with Instore and Restaurant Tech responsible for attracting $2.68 billion out of the lump sum].

This white paper provides an up-to-date overview of the restaurant tech trends and state of the play, including:

1. Food Tech and Restaurant Tech market overview with startup funding distribution downstream and upstream.
2. Use cases and new application of technologies in the food service economy sector: from AI and IoT to QR codes and NLP technologies.
3. Trends shopping the way people order, serve, cook, deliver food in the post-pandemic world: BOPIS, sanitation tech, driverless vehicle, social selling, ghost kitchens, and more.

Is this restaurant tech guide for you?

You may find the information useful if:

• You’re a franchise owner looking to optimize operations, administration and compliance spheres of your business.
• You are a software development company working on developing a restaurant management system or a connected kitchen solution.
• You are a third-party software vendor with a tech solution for the restaurant and events industry looking for ways to improve your product and distribution channels.
• You are a software development engineer working on a connected restaurant device or software product in search of insights, best practices, and use cases.
• You are in restaurant business and want to learn more about restaurant tech trends and future predictions.

While the research in this white paper aggregates statistical information on food service tech funding and the startup realm, it also offers insightful use cases and unorthodox, captivating applications of technologies in the food industry.

Interested to find out more? Download this insightful Restaurant tech white paper here.