What new organizational models have you seen or used at your organization?

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Former Chief Technology and People Officer in Software, 1,001 - 5,000 employees
I think there used to be this traditional model of similar organizations in IT, where there was an application side, and then an ops or infrastructure side. Now, there's a set of tools like BI analytics and all these workplace and employee experience tools that have driven new organizational models in which somebody higher up in the organization is owning some of these things, as opposed to it being buried in one side or the other.

In tech, what used to be IT is being put under product leadership and product engineering. Because there's this idea that since they build great products and platforms, they could do this better or more efficiently/effectively.
CEO in Services (non-Government), Self-employed
Coming from a large enterprise, it was semi-traditional in the sense that you had dev and applications, then the service side, and then comms and networking, etc. What I'm seeing now with former employers and current clients is that the overall role of the CIO has changed dramatically. 99% are digital transformation-focused or data-driven focused. And that's causing major shifts within the organization of the Industrial Technologies Office ( ITO). We are now becoming a global business unit as opposed to a services provider. That changes structure dramatically. 

We have a license to be the innovators we always were, which is also changing the organizational perspective. And what's popping up is the notion of experimentation and labs. That ownership within the organization is falling under aligned reporting of an exploration or experimentation manager—or maybe a director level—and then a VP of product engineering. But these are products to be spun off as satellite companies or to be sold off and licensed back.

That’s where we have a lot of really smart folks from every level of the organization throwing themselves at a single targeted project, which is for the global organization but will have to be deployed in phases or stages. It's basically: we need AI, but what kind of AI? And how can it be used concurrently across facilities so that all the data that we're getting back can be analyzed in an aggregate? It's a strategic and holistic approach to experimentation. A lot of the automotive manufacturers are doing this but it's mostly the largest organizations within their niche of the market.
VP of IT in Software, 10,001+ employees
I spend a lot of my time building organizational models.  Often different ones for each business as they are different, but there are some common themes...

1) Journey or Capability alignments applying both the business and technology are gaining tracking though still emerging.  Where they are maturing, some traditional IT roles are moving into Product Management.

2) End to end accountability on smaller cross functional teams (you build it you run/operate it) rather than Arch, Dev, QA, Ops being on separate. These are maturing in to Product Engineering teams (Agile Teams/Squads). 

3) Remaining teams becoming enablement teams, governance, compliance, QA, DevOps, PMO, switch from control to enablement. They are help to same metrics for speed/value as engineering. These teams enable to the engineering team to live up to its capabilities.

4) Platform architectures are impacting orgs as well, with residual infrastructure and operations (not pulled into the engineering or enablement teams above) provide platform services similar to cloud provides but not seeing them called that.  More mature also support teams dedicated to user journeys, business capabilities, and the platform/foundations.

5) Increase use of SRE teams for traditional production support roles, though few are "text book" SRE teams.  Not clear if these will mature or continue to be somewhat upskilled production support teams.

6) Increased use of small agile innovation labs to fuel innovation/speed decision making on new technologies/POCs

7) Data teams emerging as business side teams with strong dataops driven self-service data platforms emerging.

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