Data-Driven Business – a fad or a challenge?

15 July 2019

Interview with Michał Koziara, CEO at 3Soft, on the potential of data analysis.

3Soft: How do you understand the term ‘Data-Driven Business’?

First of all, to me Data-Driven Business is much more than making decisions based on reports or using classic BI systems. IT systems used in enterprises generate and collect data on every area of their business – from customer details to market environment analysis. There is a huge business potential in this data.
Since the 1990s, BI (Business Intelligence) reporting systems have been used to support decision-making. However, these are systems based on the analysis of historical data. The Data-Driven Business concept offers a completely new approach that meets today’s challenges.
Data-Driven Business consists in analyzing historical data in order to predict future business events. Due to the use of advanced statistical methods, Artificial Intelligence and Machine Learning, it is possible to identify trends with high probability, predict demand for individual products, optimize marketing activities and increase sales by adjusting the offer to the individual needs of the customer just in time. If we add the automation of business processes to this, we can talk about a transformation towards a data-managed enterprise.

Data-Driven Business consists in analyzing historical data in order to predict future business events. Due to the use of advanced statistical methods, Artificial Intelligence and Machine Learning, it is possible to identify trends with high probability, predict demand for individual products, optimize marketing activities and increase sales by adjusting the offer to the individual needs of the customer just in time. If we add the automation of business processes to this, we can talk about a transformation towards a data-managed enterprise.

3Soft: What can this automation involve?

The idea of automating business processes is commonplace. However, the Data-Driven Business concept opens up new possibilities of automation in areas reserved until now for departments working in the ‘analysis of historical data – plan – expert decisions’ model. In view of the market dynamics and the multitude of alternatives available to consumers, especially via the Internet, this model is no longer effective.
Let’s take the supermarket as an example. Automation becomes critical when it is necessary to optimally stock dozens of points-of-sale on a daily basis with a product range consisting of thousands of items based on the latest data. We can take into account such factors as: demand determined on the basis of current conditions in stores and warehouses, production and logistics capabilities of suppliers, current and planned special sales promotions and their effect, or key factors from the consumer perspective, such as weather, day of the week, holidays, store location, or the competition’s offer.

3Soft: Can any company undergo this transformation and operate based on the Data-Driven Business concept?

One of the elements of the Data-Driven Business concept are advanced statistical algorithms, so the data collected by companies must be statistically significant. This means that a certain volume of data is required and the data should be complete and of a high quality to ensure that it contains correct information.
Paradoxically, in some cases, the excess of data becomes a problem. Large organizations collect so much data, often in separate IT systems, that connecting it and finding the business context becomes a challenge. In some corporations, the question “How many clients do we have?” becomes nontrivial.
The introduction of the Data-Driven Business concept requires the development of a Data Management strategy. Modern technologies based, for example, on the Hadoop platform, allow information to be correlated independently of trading systems. This makes it possible to move away from the costly and risky integration of IT systems towards a Data Lake, which becomes a source of truth of sorts in the organization.
However, what I think is of key importance in implementing the Data-Driven Business concept is the approach of the company’s top management. The whole idea is based on moving away from manual control and relying solely on expert knowledge towards automatic decision-making by an IT system based on data and mathematics. Intuition and industry experience are replaced by advanced statistical algorithms. It takes both mental change and a certain kind of courage.

The key importance in implementing the Data-Driven Business concept is the approach of the company’s top management. The whole idea is based on moving away from manual control and relying solely on expert knowledge towards automatic decision-making by an IT system based on data and mathematics. Intuition and industry experience are replaced by advanced statistical algorithms. It takes both mental change and a certain kind of courage.

3Soft: Does starting the process of Data-Driven Business implementation cause a revolution in the company?

More like evolution. The implementation of the Data-Driven Business concept is based on open source technologies and the hardware, necessary for data collection and processing, is getting cheaper. So, in a cost-effective model, it is possible to build analytical platforms alongside the maintained IT systems that already exist in the company. The automation of processes should proceed in a controlled manner, step by step, with its effects accurately measured. This means that the business and technological risk of launching a Data-Driven Business approach may be low.

3Soft: What challenges should companies wanting to implement the Data-Driven Business concept be prepared for?

The implementation of the Data-Driven Business concept is multifaceted. It requires identification of opportunities at the business level, analysis of available and potentially available data (Data Management), determination of Business Automation methods and verification and adjustment of statistical models to specific conditions of each enterprise (Artificial Intelligence). What is more, the implementation is often cross-departmental, which requires convincing people from various departments – from sales and marketing to production, purchasing and logistics – to the idea.
In my opinion, Data-Driven Business is a concept that can be pursued, but will probably never be fully achieved. What I mean by implementing Data-Driven Business is rather moving in the right direction. So it is worth taking this first step, and then the next ones.

In my opinion, Data-Driven Business is a concept that can be pursued, but will probably never be fully achieved. What I mean by implementing Data-Driven Business is rather moving in the right direction. So it is worth taking this first step, and then the next ones.

What does the process of implementing the Data-Driven Business concept look like?

We start our cooperation with clients from the identification of opportunities in the business sense. We define goals and constraints, consider the available data and processes that can be changed through automation, taking into account the business reality of the company. We inspire and ask questions, help find the answer to “What do we want to achieve?”. At this stage, we are the active party, but close cooperation is crucial. Then, we demonstrate how the process of developing statistical models and using artificial intelligence will run, what data will be collected and processed, and how automation will proceed.
We show how we will achieve our goals so that the Client can make an informed decision on whether to start a journey towards Data-Driven Business.

3Soft: What is your advice to companies that want to start using their data to increase their competitive advantage?

Firstly, I think it’s worth starting by getting inspired. There are already many groundbreaking products out there that use artificial intelligence to analyze data. The examples include listening to music, watching movies, buying online, ordering food from home. Very often the concepts these products are based on, can also be implemented in other companies, no matter how different their business areas.
Secondly, I support the strategy of picking low hanging fruits, i.e. first implementing those business cases that can bring the greatest benefits at the lowest cost and at the lowest risk. Contrary to what may seem, when it comes to drawing business value from the data collected by companies, there are still many of them.
Thirdly, I advise them to contact us 🙂 We will help turn inspiration into action. That’s how we understand our role.