For the first time in human history the annual amount of internet traffic surpassed a zettabyte of data. According to an article, by Harvard Business Review, that is the equivalent of a hundred and fifty million years of HD video. With this unfathomable amount of data being processed, it has become vital for all businesses to develop their own strategies to maximize profits from data. The question though, is where does one start to develop a data strategy?
The first notion you must grasp is that you will have to understand your company’s data needs. The traditional dichotomy of data strategy is offensive vs. defensive. Offensive data strategy is the far more interesting of the two, with its ability to make predictive models and allowing companies to target new markets. While defensive strategy is about data security, consolidation, and reducing overhead. Now you may think you can split your company’s focus evenly between the two, but that would be a mistake. It would only serve to make both goals flounder, and not deliver the desired results. So to prevent your company’s floundering it is important to understand how your company’s data works and the restrictions you must work within.
To determine if you need a defensive approach you should ask yourself these questions. Does my data fall under strict regulations such as banking or hospitals? Do you need a standardized, and reliable, source of data that is easily extractable? If you answered yes to either of these questions you should focus on a defensive data strategy by developing a single source of truth system architecture, which will reduce overhead and make it easier to control the flow of data.
If you are not heavily regulated and are looking to grow through targeted expansion, then an offensive digital strategy is the best option for your company to focus on. Offensive strategy focuses on extraction of insight from consumer data, and as such it needs to have more flexible data. This allows the data to be more easily manipulated to produce results. As such a multiple versions of the truth architecture would be most beneficial to develop.
To balance the creation of the two strategies is difficult, but by focusing on a defensive strategy first, and consolidating your company’s data, you will have a reliable infrastructure. From there you can then build out an offensive strategy, and allocate more of your company’s resources to growth. It is easier to build out once you have control of your data then it is to consolidate when you have aggressively expanded and your data sources are all over the place in your network. HBR suggests by allocating 90% of your data budget to building a SSOT to start, and only allocate 10% for expansion. After you have developed a reliable data architecture, your company can then slowly move into the direction of an even allocation of resources. A tactic that is recommended, to maintain control for expansion, is to assign a specific CDO, Chief Data Officer, to each project that uses a different source of truth, in order to maintain data integrity.
Data strategy is no longer an avenue for your business, it is the avenue. With these basic guidelines, implementing and managing a data strategy will be easy as pie. Next post we discuss the heretical notion that too much innovation can be bad.