By Mike Redding
Consider the following scenario: A customer service manager believes the company can increase repeat sales if its customer service reps contact all customers who have purchased more than $500 worth of products in the past month to see whether they have encountered any issues the company could help with.
Ideally, the service manager makes this decision after weighing the potential benefits of the activity versus the cost involved in making the calls. If the cost is less than the incremental revenue that is likely to be driven through increased sales, the manager will do it. If not, he or she won’t.
Seems pretty straightforward, right? So, why aren’t more managers acting on these hunches every day? They don’t do it simply because most organizations lack access, expectations and time. They lack access to the necessary data, even though the cost per hour of the customer service reps’ time, the number of customers who’ve spent more than the minimum amount in the past month, and the current rate of repeat purchases most likely exists somewhere in the company.
Additionally, there are no expectations—few or no metrics or incentives exist—to help make this type of experimentation part of someone’s job. Finally, too few people have the time to act on these ideas. As a result, managers either make decisions on gut instinct or, more often, do nothing at all.
This scenario will soon change, however, since a new corporate model is quickly emerging. The crusade is being led by young and nimble companies that are not weighed down by heavyweight legacy IT systems and so are capable of infusing data into the decisions their managers make daily. In fact, these companies expect their managers to step up to the plate with proposals supported by hard data.
Within these companies, data is not tethered to a particular software application, but rather can be moved, shared with alliance partners or suppliers, divided up, analyzed any which way or blended with other data—whatever it takes to unlock its value. With data more easily available, this new breed of company has gone a step farther and created a new corporate data culture, one that regularly backs up managers’ choices.
As a result, these organizations can move more quickly and more confidently in their decision making. They can explore ideas more easily and with more conclusive results, cut costs more expeditiously and efficiently, and better evaluate and enter new markets, as well as define and launch new products.
So What’s New Here?
The truth is that businesses have been recognizing and treating data as a valuable tool for decades. The difference is that, until now, the cost to gather, aggregate, access, report on, analyze, process and store that data had presented a barrier. Organizations, as a result, had no choice but to build systems and cultures that treated data as a scarce commodity and allowed only the highest priority decisions to rely extensively on data.
Now, innovative tools and maturing technologies have altered the landscape. CIOs can architect data platforms that enable their organizations to access and share structured and unstructured data across the enterprise, at minimal incremental cost.
Implementing a data platform to change the cost model is one thing, but to get tangible results, companies must move from the current model—the implicit strategy of maximizing the benefit of a set amount of data usage—to an explicit model where all employees are expected to maximize data usage to drive business benefits.
This represents a cultural shift in how organizations operate. In this new paradigm, data becomes central to innovation and to all decision making, fueling growth and making the organization’s operations more efficient at every level. This allows employees to ask, “What data would allow me to do my job better?” It also enables management to make the necessary data available to them.