SPEED is essential for DATA VALUE but you have to be heading in the right direction
In today’s fast-moving and connected world, the need for an ever-accelerating pace of response is primarily driven by two goals: one, to satisfy customers’ demands, and two, to react to changing market conditions.
And this means speed is essential, especially when it comes to data, AI and technology. After all, insights from data are most useful when they can lead to timely interventions.
This edition of my newsletter is inspired by observations of what happens when we
chase after higher speed without considering the big picture. I believe that when we miss certain components or options, they can affect our trajectory or even become stumbling blocks later on, when we are well underway.
Balancing speed against other priorities
While it is true that customers place a high priority on fast service and that
organisations have to be aware of market developments and constantly evaluate their value proposition in order to stay competitive and act on both challenges and
opportunities, a one-sided focus on speed can come with serious pitfalls.
Just consider the scenarios of acting on incomplete information or building a “speedy” system that cannot handle the volume of data necessary to take an enterprise to the next level.
In my view, it is essential that efforts to increase speed link back to value.
It is widely acknowledged that enterprises with good data capabilities can use data to drive business success. However, in order to gain richer – and more actionable – insights, it is important that increasing speed doesn't come at the expense of the quality, quantity or security of data.
Ultimately, the quality of the decisions or actions that are based on data depends on the quality of such data – and on how it is used to drive value. Data that is riddled with errors and inconsistencies can lead not only to faulty decision-making – it can actually set the business on a wrong course.
Bulking up versus streamlining
Another conundrum presents itself when the focus is on “how quickly can we respond?” without thinking of “how much data can our system handle at this speed?” Sometimes, the solution for delivering on the first scenario is very different from the second.
