Data as a Product: Redefining How We Derive Value from Data
While it is already given how important data is for any enterprise, it is still surprising, as well as unfortunate, to see that there are many businesses that are still not cognizant of this fact. A recent survey by Wiiisdom revealed that the typical adoption rate of analytics is only 26%. This means that seven out of 10 business leaders are inclined to make critical decisions based entirely on their gut rather than on data.
And this gut-based decision-making sets the stage for failure and frustration for not taking into account a variety of factors. Factors that would have been taken into account if these managers utilized the data they would have had, thus ensuring more informed decision-making that generates the results they were hoping to achieve.
Is the Chief Data Officer to blame?
So why are many decision-makers not making use of the data as it’s supposed to be? Why does data remain undervalued given its importance in today’s environment? Already, some pin the blame on the corporate structure, particularly the presence of the Chief Data Officer (CDO) itself who is being seen as largely ineffective in the grand scheme of things.
It must be said first of all that the CDO role is not necessarily a redundancy in the corporate structure. Rather, it should be seen as a positive sign that the company is ready to take data seriously. What makes them ineffective in their role, however, is that their duties and responsibilities are poorly defined with unclear expectations. This is compounded by the fact that in most cases, their tenure is short and turnover for such roles is quite high.
In addition, CDOs typically come from technical backgrounds. As a result, their immediate focus tends to be on defensive data strategies, thus the value they create is difficult to measure in business terms and invisible to most internal users. As such, business executives who seek immediate ROI won’t appreciate the output CDOs tend to deliver, not to mention the length of time involved.
It also does not help that most decision-makers, especially those from non-technical backgrounds, have difficulty articulating the solutions they need. They have a clear idea in their minds but they are unable to express them because they have little to no idea as to what solutions are possible. Besides, there is already a dedicated data team responsible for translating those ideas into reality so such work can be delegated to them instead.
Should there be a data literacy course?
Given this particular knowledge gap, one might think that a data literacy course might help address this issue. But this is actually a huge ask, one that is not guaranteed to work for several reasons. One key reason is that data literacy programs are not incorporated into enterprise strategy, while others are treated as side projects that are not given the attention they deserve.
Then there is what happens after training wherein chances are whatever was taught in the training will be forgotten after a week or even shorter. It also doesn’t help that there is a lack of on-the-job practice that will allow them to apply what they learned in the real world.
Redefining how we look at data
Knowing the challenges in utilizing data in the workplace, what needs to be done to effectively address these challenges in realizing the goal of a data-driven enterprise? One factor that is evident in these challenges is how data is being viewed which is a company project more than anything. That needs to change.
There is a need to redefine the business’ relationship with data and produce insights that are more accessible to users than gut instincts alone, helping them make better and faster decisions. That entails a shift in perspective and treating data as a product that is accessible, visible, and usable for everyone.
The characteristics of a product and how data benefits from these characteristics
A product is defined as an item or service being offered to serve real customer needs better than the alternatives. And a successful product is specific as to who will use it, how it will be used, what jobs it will help accomplish, what pain points it will address, and how it will generate revenue. And customers consistently buy, use, and recommend a good product, enough to sustain its growth and profitability.
Companies can unlock the full value of their data by applying the principles of product to their data, thus encouraging users to utilize data in their work. Of course, there is much work that needs to be done in creating this shift. Primarily, there is a need to understand the job the analytics helps get done, desired outcomes, and the user experience. The way analytics is delivered should be reconfigured so there are a clear set of features, user experience, and value proposition that meets the target users’ needs so that they will be enticed to adopt it.
Laying the groundwork that will ensure this shift towards data as a product mindset will result in a complete turnaround in the adoption, attitudes, perspectives, and behaviors of staff around data, thus achieving the goal of being a data-driven business that is geared towards future success and growth.