\u201cUse cases are dead.\u201d
\nThat was the line that actually stopped me in my tracks, well, I was sitting down, but you know what I mean.<\/p>\n
I heard this at the Collibra Data Citizens event this week in London.<\/p>\n
It came from a panelist at Accenture, and the more my mind churned through it, and the more I explored it, the more I agreed.<\/p>\n
Because if you know me, I write and speak about use cases all the time. Getting new input is always good, as it tests your assumptions. Clearly, it tested this one. So I’m exploring this thinking further.<\/p>\n
The problem isn\u2019t that use cases lack value; it’s that most organizations treat them like proof points rather than operating principles. This plays deeply into my belief and writings that the operating model is key here<\/p>\n
Many companies chase quick wins, measure short-term ROI, and then move on to the next shiny problem.<\/p>\n
But that\u2019s not transformation, that\u2019s just experimentation in my opinion.<\/p>\n
If you want lasting value, a use case has to be integrated into the value chain. This is obvious and something I have advocated for, but my resolve around this now is even greater.<\/p>\n
It has to move from \u201ca project we did\u201d to \u201cthe way we work,” and that means designing it to live beyond the pilot.<\/p>\n
Here are three things leaders need to think about if they want to break the \u201cone-and-done\u201d cycle:<\/p>\n
1. Anchor use cases to business outcomes, not capabilities. Too many start with \u201cwe\u2019ve got a model\u201d or \u201cwe\u2019ve got a dashboard.\u201d The right question is: what decision or behavior does this change in the business? When a use case is built around an outcome such as improving margin or reducing risk, it naturally links to accountability, investment, and process.<\/p>\n
2. Build integration paths, not showcases. Success stories are nice, but sustainability comes from embedding. That means connecting the use case into core workflows, aligning data and tech enablers, and assigning ownership to the business and not to a project team. A churn prediction model, for example, only matters if it automatically triggers retention workflows, feeds service scripts, and adjusts incentive plans.<\/p>\n
3. Design for reuse and scalability. Every use case should contribute to a reusable asset such as a data pipeline, a policy, a governance rule, or an automation pattern that others can build on. This is how an organization compounds its intelligence over time rather than recreating it project by project.<\/p>\n
Exploring this deeper in your organization will help change the conversation.<\/p>\n
Companies are walking into an AI world or nightmare, which may well end in wasted pilots, fragmented processes, and cash going down the drain. Well, I’m sure plenty are!<\/p>\n
So don’t ask yourself \u201cwhat\u2019s our next use case?\u201d<\/p>\n
I think the ultimate question should be \u201chow do we embed intelligence into the way value flows through the business?\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
\u201cUse cases are dead.\u201d That was the line that actually stopped me in my tracks, well, I was sitting down, but you know what I mean. I heard this at the Collibra Data Citizens event this week in London. It came from a panelist at Accenture, and the more my mind churned through it, and […]<\/p>\n","protected":false},"author":546,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[10],"tags":[],"acf":[],"yoast_head":"\n