I may be a little biased on this subject, but I truly believe that understanding the value of data should be a major priority for just about any organization in today’s business environment.
Clearly, organizations have other core elements that help to define them — namely, people, processes and technology. But data sits at the heart of everything, and without it none of the other elements could be productive.
But it’s one thing to make such a statement in general terms, and quite another to actually do the work to understand the value of data within your organization and then take advantage of it.
A timely question
This is not just an academic question — in fact, there’s a real sense of urgency to it, driven by the demographics of the workforce. Workers in the Baby Boom generation are retiring in huge numbers, and organizations in every sector are dealing with the fallout. In fact, there are entire organizations that are being stood up simply to consult on the complex issue of knowledge transfer between the retiring Boomers and their younger co-workers.
But the part of the generation “changing of the guards” that often goes unaddressed is the incredible amount of “tribal knowledge” regarding organizational data that the throngs of retiring employees could take with them.
Fortunately, there are ways to gather this metadata that are not only effective in understanding the value of data, but that can also help organizations address inter-generational workforce issues, and gain other valuable insights into their people, processes and technology.
To be effective, this effort requires a specialized communication process that focuses on working face-to-face with employees in the data community over a period of time. This process allows the stakeholders to collaborate around the data, and eventually produce the kind of metadata that provides context around the organization’s data, as well as insights about the people soon to be retiring that might be helpful in future hiring or staffing decisions.
Understanding the value of data can also play a critical role in an organization’s Mergers & Acquisitions (M&A) activities. Using data valuation and infonomics, an organization can gain a much more accurate view of the value of a company it is considering acquiring. In fact, any thorough view of the target organization should include a data certification process, and an analysis of how well the two organizations’ data will mesh. It’s the difference between being able to compare apples to apples versus comparing apples to say, smoothies.
By the way, as important as this point is in today’s market, my sense is it will become even more important in the near future. If economists’ general projections are accurate, and we are cycling into another economic downturn, effective data valuation can give an organization much better insight into which M&A opportunities will best position them to manage risk in a turbulent market.
But most of all, understanding the value of data can play a pivotal role in helping an organization improve its chances of monetizing data. In doing so, it can help create entirely new revenue streams, position the organization to outcompete competitors, and possibly even generate enough revenue to buy the competition when appropriate.
The key is to focus on being good at the things that only you can do, and at least consider outsourcing the rest. No one is more experienced than you and your people at acquiring and caring for your data. But the next level of opportunity is to develop the metadata and algorithms needed to derive advanced insights and data models that are uniquely yours, and that you can monetize without risk. Depending on the data analytics skill sets you have internally, that development may indeed be something worth outsourcing.