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The modern world is developing and becoming smarter. At the same time, data is becoming a key tool for gaining a competitive advantage. The quality of data and analytics use, and the latest technologies introduction directly affects business competitiveness.

Data is a valuable business asset that transforms workflows. Almost every company, no matter the size, should be involved in data-related activities. In this case, each such company must have a clear and effective strategy for working with data.

It is essential to start working with data with a strategy. At the moment, part of the business and their leaders are simply collecting as much data as possible, because of the hype around Big Data. However, they do not think for what purpose they are doing it. The second part of the business is so overwhelmed by the data provided opportunities that they deliberately move away from solving this issue.

At the stage of developing a strategy, firstly it is important to understand what the company wants to achieve and what data can help to do it. It does not matter at all what data is already collected and is being collected now, what data are collected by competitors, what type of data is available. Data can only be useful if it meets specific business needs, helps achieve a goal, and thus creates value. Therefore, to avoid collecting useless for a particular business data, it’s necessary to focus on the goals, problems and issues that need to be solved with the help of the data.

Many companies use data processing strategies in areas of business such as marketing and sales. However, this is not enough – a plan is needed for the entire company. There is also a perception among executives that data and analytics are IT department’s responsibility. That is, managers are shifting responsibility to IT specialists. In fact, it doesn’t have to be that way. The responsibilities of IT technicians include storage, ownership, access, and data integrity based on strategic goals set by business leaders.

Key points in data strategy development:

1. Data needs. To understand what data needs to be collected, first of all, it is necessary to determine what it is for. Different types of data may be needed for each specific purpose.
2. Data searching and collecting process. When goals are defined, it’s possible to start thinking about finding and collecting suitable data. At the moment, there are many ways to do this: buying external data, using internal data, introducing new collection methods.
3. How the collected data is transformed into analytic data? To extract business ideas, it’s necessary to understand the process of applying analytics to data.
4. Requirements for technological infrastructure. The next step in the strategy development process is choosing the hardware and software that will enable an efficient data management process.
5. The level of data expertise within the company. Getting the most out of the data requires certain knowledge and skills. This issue can be resolved with the help of internal resources of the company or the involvement of specialists from outside.
6. Data governance. Working with data, especially personal data, presupposes strict adherence to the rules and regulations. It is critically important to consider and ensure security, privacy and data integrity when developing a strategy.