{"id":2153,"date":"2025-05-13T16:46:06","date_gmt":"2025-05-13T16:46:06","guid":{"rendered":"https:\/\/solutionsreview.com\/thought-leaders\/?p=2153"},"modified":"2025-05-13T16:46:06","modified_gmt":"2025-05-13T16:46:06","slug":"stop-building-use-cases-in-reverse","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/thought-leaders\/stop-building-use-cases-in-reverse\/","title":{"rendered":"Stop Building Use Cases in Reverse"},"content":{"rendered":"<p id=\"isPasted\" style=\"text-align: justify;\">I mentioned in a post this week that I would write a longer article that would cover the extent of the problem I see in many organizations that attempt to do any form of data transformation, or data strategy etc.<\/p>\n<p style=\"text-align: justify;\">Let me be clear, this isn\u2019t anything new. Many organizations have been told to build use cases to unlock the value of data and AI. Again, this isn\u2019t anything new. I\u2019m not saying that they haven\u2019t, many know, and in fact many choose to forget.<\/p>\n<p>Why? I ask you say.<\/p>\n<p>Because many build their use cases \u201cbackwards.&#8221;<\/p>\n<p>Instead of starting with business outcomes and value, they started with:<\/p>\n<ul type=\"disc\">\n<li>\u201cWe\u2019ve got this data; what can we do with it?\u201d<\/li>\n<li>\u201cWe\u2019ve just launched this platform, what use cases can we spin up?\u201d<\/li>\n<\/ul>\n<p>What has the result been? Loads of activity and hubbub! Sounds great right?<\/p>\n<p>But in \u00a0reality, the outcome tends to be \u201cnot enough impact.\u201d<\/p>\n<p>So how do we flip the model?<\/p>\n<h4><strong>Four Layers to Build Use Cases That Deliver<\/strong><\/h4>\n<p style=\"text-align: justify;\">I\u2019m just going to call this a \u201cvalue-led use case framework\u201d which has four distinct but connected layers:<\/p>\n<ol start=\"1\" type=\"1\">\n<li>Business Use Case<\/li>\n<li>Solution (Product or Algorithm)<\/li>\n<li>Data Use Case<\/li>\n<li>Technology Use Case<\/li>\n<\/ol>\n<p style=\"text-align: justify;\">This isn\u2019t just a nice hierarchy. Its purpose driven and hangs off the North Star which is the business use case. This is the value piece, whether that\u2019s revenue\/growth focused, or looking at cost efficiencies etc. This is the discipline and focus that is required, and one that that separates wasted investment from real ROI.<\/p>\n<h4><strong>Business Use Case: Anchor to Outcomes<\/strong><\/h4>\n<p style=\"text-align: justify;\">Every use case should begin with a crisp, commercial intent. It should answer the fundamental question:<\/p>\n<p>What are we trying to achieve?<\/p>\n<p style=\"text-align: justify;\">Is it revenue growth, cost reduction, improved customer experience, risk mitigation? Just as I explained in the previous paragraph.<\/p>\n<p>So, what do business use cases sound like? They typically sound like this:<\/p>\n<ul type=\"disc\">\n<li>\u201cWe want to reduce customer churn by 10 percent in the next 12 months.\u201d<\/li>\n<li>\u201cWe need to shorten onboarding time by 30 percent for new merchants.\u201d<\/li>\n<li>\u201cOur aim is to improve early fraud detection by 20 percent in real time.\u201d<\/li>\n<\/ul>\n<p>What are the distinctions here?<\/p>\n<p style=\"text-align: justify;\">There is absolutely no mention of AI, cloud, machine learning, dashboards etc, just the business challenge or opportunity. You can even spin up a problem statement as part of this phase and tie it back to a specific business problem.<\/p>\n<h4><strong>Solution (Product): Deliver the Outcome<\/strong><\/h4>\n<p style=\"text-align: justify;\">Now that we know the business problem, opportunity, problem statement etc., we can now start to shape the response. Are we focused on creating:<\/p>\n<ul type=\"disc\">\n<li>A churn prediction model<\/li>\n<li>A self-serve onboarding portal powered by intelligent workflows<\/li>\n<li>A real-time fraud scoring engine<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Some solutions are algorithms, some are tools, \u00a0and some are full-on products. What matters is that they directly support the business outcome as described.<\/p>\n<p style=\"text-align: justify;\">I often find this step often gets skipped when teams are in a rush to play with data or deploy the latest tech stack. You can see the legacy of this type of rushed decision making in the adoption of products, no real ROI, and loads of shelfware lying around!<\/p>\n<h4><strong>Data Use Case: Fuel the Solution<\/strong><\/h4>\n<p style=\"text-align: justify;\">Once you have defined the business outcome and the solution, then you can identify what data is actually needed. It\u2019s not just the data that you have, it might be external types too. So you need to think about what you need and why.<\/p>\n<p>Think about it through three simple questions:<\/p>\n<ul type=\"disc\">\n<li>What data sources are critical?<\/li>\n<li>Where is the data?<\/li>\n<li>Is it trusted, timely, accessible?<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Here\u2019s the other benefit in looking at it this way, data quality becomes a business conversation, not a technical one. Because it\u2019s now tied to a clear outcome.<\/p>\n<h4><strong>Technology Use Case: Enable Efficient Execution<\/strong><\/h4>\n<p style=\"text-align: justify;\">Finally, and only now comes the tech chat. I bet you have been gagging to talk about tech from the beginning! Nope, leave it out of the conversation, we need to think wider than the tech piece, and remember, it\u2019s an enabler and that\u2019s why it\u2019s the last point.<\/p>\n<ul type=\"disc\">\n<li>Do you need real-time APIs or batch jobs?<\/li>\n<li>Do you need MLOps or a lightweight scoring engine?<\/li>\n<li>What\u2019s the simplest tech stack to achieve the goal?<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Yep, and you know it too, that many organizations start here, trying to retrofit value into architecture. But architecture without purpose is just expensive design.<\/p>\n<h4><strong>What Happens When You Flip the Flow?<\/strong><\/h4>\n<p>You get huge advantages from this value led conversation, some of these are:<\/p>\n<ul>\n<li>Clearer prioritization<\/li>\n<li>Faster time to value<\/li>\n<li>Better stakeholder alignment<\/li>\n<li>Less AI hype, more AI delivery<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Most importantly, you get outcomes that matter to your board, your business stakeholders, the C-Suite, external stakeholders and not just the data team.<\/p>\n<h4><strong>Bottom Line<\/strong><\/h4>\n<p style=\"text-align: justify;\">If your AI and data teams are struggling to show value, don\u2019t focus on building pipelines or models. Focus on business intent.<\/p>\n<p>Ask the question that too often gets skipped:<\/p>\n<p>\u201cWhat problem are we solving, and why does it matter to the business?\u201d<\/p>\n<p>That\u2019s where every successful use case begins.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I mentioned in a post this week that I would write a longer article that would cover the extent of the problem I see in many organizations that attempt to do any form of data transformation, or data strategy etc. Let me be clear, this isn\u2019t anything new. Many organizations have been told to build [&hellip;]<\/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":"<!-- This site is optimized with the Yoast SEO plugin v23.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Stop Building Use Cases in Reverse<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Stop Building Use Cases in Reverse\" \/>\n<meta property=\"og:description\" content=\"I mentioned in a post this week that I would write a longer article that would cover the extent of the problem I see in many organizations that attempt to do any form of data transformation, or data strategy etc. Let me be clear, this isn\u2019t anything new. 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