Data Governance, Business Analytics Drive Smart IT Decisions

Suppose you had a clean slate to work with. How would government IT look different? How could it be improved upon? We asked state and local government technology leaders just that question.

It’s more than just a thought exercise. Their clean-slate wish lists help to paint a picture of what might be possible. From governance structures to funding mechanisms to hiring schemes, they describe a range of creative changes that could help to put IT on a stronger footing going forward.

To see all responses, click here.

If you could start a government IT shop completely from scratch, what key steps would you take? What would you change?

I would take two different steps, but they’re closely related. First, I would make sure that we had a really robust business analyst group. We have plenty of project managers, but they tend to be more like taskmasters: Did this meeting get scheduled, did this task get completed? It’s not so much about analyzing opportunities to embed technologies or to leverage standard platforms.

My second thought is to bake in the governance strategy at the front end, with a formalized team including data governance specifically. Particularly in the public sector, we need to think about data security, privacy concerns, data reporting. Data integrity with integrated systems is really critical, and right now it tends to be an afterthought.

That would include some automation as well. If you’re starting from scratch, you would probably have standard platforms, a standard data dictionary, perhaps AI tools with retention rules baked in.

Why would this approach be better than your present setup, or better than the current norms?

The reality of public-sector budgeting is that it tends to be driven by budget cycles, whether it’s a one-year cycle, as with most jurisdictions, or some now have a two-year cycle. Either way, you’re always planning at least a year ahead. What tends to happen is technologies get replaced in alignment with those budget cycles, rather than holistically on a platform-by-platform basis.

If you were starting from scratch with business analytics, governance structures and a common platform, a common data dictionary, then you would add features for specific processes. It’s just a better design than if you build out each of those separate processes with a separate project charter.

It’s not just a pure tech advantage. It’s also a practical advantage in terms of prioritization. Who decides which projects you should focus on? By having that business analytics and a governance structure, along with the common platforms and data structures, you’re much more likely to get the right answer in terms of focusing on the stuff that matters most, first. Rather than giving projects priority just because there’s money available, you would instead be putting the highest priority projects first.

What challenges would this new model encounter, and how could these be overcome? What would it take to make this real?

There are very real barriers to this. One is always money: Not just budget availability in the sense of revenue versus expenses, but also in terms of priorities. In government, prioritizing IT hires versus jail guards or nurses at the hospitals is always a real struggle.

We’re not necessarily at the forefront of the policymakers’ minds in terms of areas to invest in. That’s been historically true. In the context of data governance, I just don’t think that it is viewed by all executives as being critical.

It needs a paradigm shift, by which I mean that IT needs to be seen as a strategic partner. It can’t be an afterthought. When IT is seen as a partner — we are here to leverage technology, to make that vision a reality — then people can see the importance in investing in this kind of organizational infrastructure.

Tom Lynch has worked for Cook County IT since 2014 and served as CIO since 2018. His previous work includes public- and private-sector roles in the Chicago area.