In the digital age, business success often relies on a magic ingredient. Whether they put it to use (or even realize they have it at their disposal), most companies possess it: data.
Companies generate data every day through their operations, but many aren’t aware of its huge potential. That’s where companies like Adastra come in. The Czech-Canadian leader in data management helps businesses unlock opportunities to use their data and leverage its business value.
David Kalab, Adastra’s Vice President of Data Management, heads up a team of 400 people who strive to help customers achieve gains from utilizing data. Expats.cz sat down with David to learn more about trends in the data sphere, the impact of AI on data management, and his recipe for companies eager to put their data to work.
How does Adastra help companies gain an advantage from data?
Adastra is a Czech-Canadian company, founded by three Czech owners in 1997. We’ve always been a data company; our portfolio is wide now, but we see great business value in data and how it can help organizations become better. Around 90% of our customers are companies that stay with us for a long time and there is a reason they do so.
In the beginning, banks, insurance companies, and telecom providers were our major segments. As time went by, we started working with all segments; our biggest customer in Czechia today is in the automotive industry, and manufacturing is now our fastest-growing segment.
I joined Adastra in 2005 as a data consultant and later started managing projects. Last year, Adastra went through a reorganization, and I became the leader of Data Management, the biggest group of people handling data in Czechia.
Which industries are the forerunners in using data?
There are segments and sectors that have already been substantially data-penetrated, and there are others where this is happening now. Historically, banks and telecom companies were the leaders. But the biggest movement today is in the energy and manufacturing sectors.
The production costs of manufacturing, especially automotive, create huge opportunities for data in manufacturing. Industry 4.0 and production lines all produce data. Companies that optimize how they move goods within their supply chain will gain market share over those that don’t.
What are the benefits of a data management partner?
We examine data and its potential benefits from various angles. The number one question is typically: “How do I get more customers?” We look at where the opportunities are, and where data analysis can give us an advantage over competitors.
Number two is: “What are our customers willing to pay for, and how can we gain greater revenue?” This can involve bundling products and identifying where the greatest profits are. The third issue is cost savings: “How can our company optimize costs without impacting quality?”
In manufacturing, predictive analytics enable us to examine production lines, catch anomalies, and prevent them from affecting operations. Cost and time savings in the supply chain can be achieved; one cost-saving project that we undertook, for example, involved analysis of the loading of containers; we figured out the best way to load the containers in order to minimize unused space.
This leads us to ESG, another major topic. This requires capturing new types of source data and using it for business purposes; how can I make my product greener and more sustainable? In marketing, data can enable customer segmentation to create personalized offers.
How is Artificial Intelligence (AI) affecting the data sphere?
Whether it's AI or GenAI, it’s a big phenomenon. If a company uses AI – and there’s potential in every segment and type of operations – it can work more efficiently, cutting out repetitive tasks, while taking better care of customers.
There’s also a lot of potential for creating new “AI customers”; products with embedded AI. You could have a dishwasher with AI, for example, which automatically orders new washing tablets for you.
To benefit from all these opportunities, you need data - and that data needs to be of good quality. AI costs a lot of money to implement, so if you don’t have quality data, there’s a risk that you’ll lose more money than you gain. Even if you have good data, you need to adjust how your organization operates, including supply chains, to accommodate the new technology.
You have lived and worked in the USA; how does the Czech tech scene compare?
Czech technical universities are of very high quality. Whether it’s data engineers or AI engineers, there’s a lot of potential and quality being produced, and many tech start-ups have succeeded.
The difference I see is the fundamental approach - how much we believe in what we do. In the States, I saw a mindset in which people were very confident about their work and achievements, and they were confident about promoting them.
Innovation gains far greater momentum in America. Companies take innovation very seriously; they want to be the first to achieve something. After all, with this mindset, your business could become the next unicorn. You have to accept the risk of failure, knowing that if you don’t try, you’ll never be at the forefront.
Here, people think their ideas need to be bulletproof; they need to be sure that the things they make work 100 percent. As a result, they sometimes hesitate to promote their work and go to market with new ideas that could succeed.
Do you feel you have brought some of that American approach to your team?
I’m trying hard to do this. I like the American mindset, and I try to be progressive in our approach here at Adastra.
Whether it involves shaping teams in new ways or bringing in new competencies and capabilities, we need to innovate constantly. Forgetting about this need will lead to other companies jumping ahead. Constant improvement and innovation cost a lot of money, but they make us the company with the widest set of data competencies. Regardless of which hyperscale you use, whichever technology you use, and your business problem, we’ll be able to put the puzzle together for you.
What’s your recipe for businesses wondering how to use data?
Some traditional businesses still haven’t realized that they should use data, mainly in certain types of manufacturing. This comes down to ownership and management. If you get the answer: “I know how this business works; I don’t need any data,” you’re already losing, because other companies in your segment will use data to optimize and gain faster insights. Data costs money – but there’s a reason why so many companies are using data to their benefit.
My recipe would be: Don’t be afraid. You can start with small projects – you don’t have to invest millions initially, but you can gain proof that data can help you.
Companies often respond by claiming they use old systems and don’t have any data. But everyone can start somewhere. The first step is hiring competent people who can help you and having a competent partner onboard you on this journey.
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