Organizations develop business strategies in order to maximize profit, minimize cost, and manage risk. Lately, a need for data-driven transformation has been realized as it has proven pivotal in materializing business challenges. Organizations therefore need to put in place a strategy on how to implement data-driven transformation in order to ensure a consolidated way to manage and fully leverage value from their data. We at Empirisch Tech help organizations to build and execute a stage-wise strategy to incrementally achieve a full data-driven transformation.
Today there is much excitement about using analytics against reams of data to gain better insight. The hope is that more data will keep us from guessing about what is most suitable for our target audience because it allows us to focus on nuanced solutions tailored to our audience. Therefore, the organizations are transforming towards making decisions deduced purely from insights gained from the data, term famously coined as data-driven transformation.
The need for a data strategy cannot be emphasized enough. Absence of a data strategy results in an organization having various financial figures contradicting across it various departments. I.e., each department and each person within each department will develop his/her own financial chart of accounts and there would be no single source of truth.
Recently much emphasis has been done on managing data as a physical asset. This is to help organizations to more accurately build the potential cost, revenue, and risk affiliated to data and its management. In order to define and track data consistently and authoritatively, several data management domains has evolved. These domains focus, for example, on defining data succinctly; ensuring its quality; keeping data secure and ensuring its privacy; conveying how data is stored, exchanged, and consumed; and creating more formal roles and responsibilities for managing data.
Organizations begin by asking themselves questions about their goals and often develop approaches based on their values, and vision thereby, define their go-to-market strategy. Companies operate either defensive or offensive strategies in regard to their data strategy. An organization that has a business strategy more focused on revenue and profit might develop a data strategy that is more offensive, whereas one with a business strategy more geared toward compliance might develop a data strategy that is more defensive. For example, the five-forces competition model is as well known approach to strategic thinking in modern-day organizations which helps them to decide on how to operate in a specific market.
