Key #4 to ITFM Implementation Success: “Good Enough” Data

good enough ITFM data

Purchasing and implementing an ITFM tool, along with building a sustainable ITFM program, can feel like an overwhelming feat (especially if you feel your ITFM data isn’t “good enough”). Establishing a project plan and tackling one step at a time can make your ITFM implementation possible. If you haven’t been following this blog series from the start, be sure to first read the following:

Step 1: Steering Committee

Summary: The success of an ITFM project starts with prudent and informed decisions. It’s critical to create a steering committee composed of multiple perspectives, allowing stakeholders to engage and collaborate toward shared objectives.

Step 2: Strategic and Tactical Alignment

Summary: Many ITFM projects are derailed by a misalignment of strategic and tactical goals- often disagreement between IT leadership and ITFM staff. Avoid this costly mistake by developing a solid strategic plan, communicating it with stakeholders, and welcoming feedback before embarking on an implementation.

Step 3: Proof of Value

Summary: Before proving value of your ITFM tool and program, you must establish within your organization what value looks like. Once stakeholders have voiced their objectives, identify quick wins to show how IT cost transparency can help the succeed in their jobs.

And now, onto Step 4- overcoming good versus perfect data, a common obstacle to getting started.


In many cases, ITFM projects don’t get off the ground because people feel the data “isn’t good enough yet.” Data gaps – missing records and missing values in key fields required for standard ITFM calculations – can indeed halt an ITFM implementation if not corrected but attaining perfect data for the entire organization before beginning is not a reasonable approach.

Everyone wants the best data possible. But it’s important for the ITFM project to get in motion with the data you have, even if it’s not complete. In fact, it’s often impossible to correct all conceivable data gaps before kicking off a project – many are revealed during the project itself and you may waste years of lost opportunity before you’re ready.

Fortunately, by limiting the scope of the initial deployment, you can limit what must be initially corrected, while still producing quality artifacts and initial value. This creates enthusiasm, boosts buy-in, and drives overall ITFM momentum.

  • Limit Scope
  • Produce Quality Artifacts and Value
  • Create Enthusiasm and Momentum

Allow yourself to accept data that is “good enough” to get started. Striving to achieve perfect data can lead ITFM teams into “precision traps.” Balancing precision and simplicity is the next step to a successful ITFM implementation.  Don’t want to wait for the next blog? Download the full eBook now.


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