Mission success for military and government increasingly depends on delivering the right insights from the right data to the right people at the right time. The problem is most agencies struggle mightily to stand up the behind-the-scenes capabilities to do that — namely, data management.

This is largely due to how agencies traditionally buy technology solutions and capabilities. For example, to kick off an acquisition, most agencies develop requirements for a data management system. Then they choose a solution based on how well a written proposal articulates how that solution meets those requirements.

The problem is this approach provides minimal visibility into the capabilities, limitations and real costs of a particular system until after they’ve acquired it.

If the solution they select is custom-developed, and therefore proprietary, there’s a high likelihood there will be challenges operating within existing IT infrastructure. Data ingested into a proprietary system creates an obstacle to effective data management because it becomes essentially walled off from other systems.

In many cases, even the customer agency is restricted in what it can do with the data once it is in that proprietary system. And any subsequent decision to transition to another vendor will come at huge expense and disruption.

Furthermore, these highly customized systems usually come with extensive — and expensive — service agreements requiring contract staffs to be on hand.

The good news is there are welcome changes afoot in how some agencies are starting to think about and procure data management capabilities.

I recently participated in an acquisition with a Defense Department organization that will remain unnamed. The contours of this agency’s acquisition approach hold great promise for improving how agencies define the capabilities they want, procure solutions that actually deliver those capabilities, and create conditions for greater trust and partnership with their vendors.

The agency published a request for information that listed dozens of requirements. After RFI responses were received, the agency invited select respondents to demonstrate their solutions before a panel of managers and end users. The agency learned from those RFI responses and demos, then further refined its requirements and issued another RFI, validating what industry could deliver and reducing the pool of viable solution providers.

It was evident that agency decision-makers learned much throughout the process about the state of the market, where technology is today and where it is heading. They learned what questions they were not asking but should have been asking to get a better-fitting solution. They also learned that some solutions cannot do what they say they will do.

This “show me”-style acquisition approach — coupled with continuous refinements to the requirements — achieves many critical objectives. The customer agency develops a sharper sense of the capabilities it truly needs, avoiding after-the-fact customizations and added costs.

During this process, many agencies may discover, for example, they do not need to buy associated support services because they can instead make needed modifications as a simple self-service. Under traditional acquisition approaches, agency buyers may not have learned to include self-servicing capability as a requirement.

When agencies can truly see for themselves what today’s offerings can and cannot do, they ask far better questions, develop far better requirements, make smarter investments, avoid unnecessary costs and ultimately end up with capabilities more aligned to their operational needs.

Agency managers know they can be more effective when they incorporate data-based insights into their decision-making. But the complexities involved in planning and acquiring advanced data management capabilities require agencies to adopt smarter tactics when exploring the market. Employing demonstrations, creating robust learning opportunities and viewing requirements-setting as an iterative process are tactics that will pay great dividends in the long run.

Jim Norwood is a retired U.S. Army colonel who managed numerous data integration and management projects for various Army, Defense Department and intelligence organizations over a 23-year career. Currently, he is partner and COO at A3 Missions, a data management company, in Augusta, Ga.