Data-Driven Enterprise – What, Why, And How
Being data-driven is a good idea for businesses looking to optimize their assets and growth prospects. In fact, it is fast becoming a widely-accepted system to improve the day-to-day workflow management. Organisations want to be data-driven – they want to be guided by data. While there is a massive amount of data being gathered, simply “having data” does not make one a data-driven organisation. It needs to be much more than that.
There are several aspects to a data-driven enterprise. Today, let me talk more about those.
What Is a Data-Driven Enterprise?
Simply put, any business which makes use of analytics to arrive at decisions is a data-driven enterprise. Of course, it’s not as easy as it seems. But basically, they use data for strategic decision-making. Now, what kind of data is it? It is reliable, relevant, accurate, replicable, and has all the other necessities to be called solid, quality data. In one of my earlier posts, I had written about data scientists. They play a huge role for a business to become data-driven. If they are able to provide worthy data, more than half of the task of becoming a data-driven enterprise is already achieved.
Why Is It Necessary?
Data-driven enterprises can easily tackle a whole lot functions thanks to their analytical decision-making ability. A paper published by MIT’s Sloan School of Management states that data-driven decision-making results in 5-6% higher productivity and output, for a business than its investments in information technology and more like those.
Being data-driven, businesses can keep an eye for prospective clients as they have an upper hand at knowing the inside market conditions. This helps set the company apart from its competitors and gives it an image of one which is well informed, competitive, and reliable. Needless to say, it also assists in serving the existing customers since they are better understood and hence, served even before they raise their concerns. That is the power of quality data. It provides a business with such smart details that every department can benefit from it – right from Marketing to Finance to R&D – enabling the business as a whole to make an in-depth analysis of market conditions and eventually even predict market trends.
How to Become a Data-Driven Enterprise?
Using the right tools is a prerequisite for this objective. However, even before selecting the tools, it is imperative to develop a strategic plan of the objectives the business wishes to achieve. Accordingly, then, the tools need to be decided. For example, Warby Parker, a retailer of prescription glasses and sunglasses, was initially using Excel for computing the key metrics. However, as the company grew, it became virtually impossible to collate the regularly increasing humongous amount of data. Their analysts finally shifted to using MySQL relational database. This helped the company immensely to continue producing an in-depth analysis of the data procured.
Second, it is important to adopt data and analytics across all levels in the company by having data-led practices. It actually means sharing vital information with fellow colleagues so that everyone together benefits from the varied bits and pieces received from a chunk of data. Unless and until data flows from various hierarchies in a business, it might not be possible to gain the real positives of becoming a data-driven enterprise; having only a couple of departments using analytics to function will never do any good for achieving the final targets of the business plan.
Third, train the staff on using data in their daily work place. Once everyone has access to the data which is relevant to their department, the overall productivity of the business is bound to increase. Take this for an example. Sprig, a food-delivery company in SFO, uses an analytics platform. Now, even their chef has access to this data to study what kind of meals are popular, which ingredients or flavors are more preferred, and then use this information to plan the menus! Imagine the benefits the company reaps thanks to not just by being data-driven but by training its staff to use the data at hand.
Before I conclude, I would like to make a very important point here. Being data-driven does not mean only having a set of systems or practices which make use of some xyz data to function. It also involves having a daily work culture which believes in functioning analytically. When everyone on board believes in the results of good, quality data, it will show through all their individual actions. Thus, every employee of the business, right from its head to the accounts person to the marketing trainee needs to get involved in the process and apply the data-driven systems to fine-tune their productivity.