{"id":1963,"date":"2025-02-18T14:25:37","date_gmt":"2025-02-18T14:25:37","guid":{"rendered":"https:\/\/solutionsreview.com\/thought-leaders\/?p=1963"},"modified":"2025-02-18T14:26:39","modified_gmt":"2025-02-18T14:26:39","slug":"strategy-isnt-what-i-thought-it-was-and-many-still-get-it-wrong","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/thought-leaders\/strategy-isnt-what-i-thought-it-was-and-many-still-get-it-wrong\/","title":{"rendered":"Strategy Isn\u2019t What I Thought It Was and Many Still Get It Wrong"},"content":{"rendered":"<p>Back in 2002, I was thrown in at the deep end, tasked with creating a data strategy for a global business I worked for. At the time, I thought &#8220;strategy&#8221; was just a sophisticated way of saying &#8220;plan.&#8221; I believed it was about mapping things out in a structured way, like a detailed blueprint.<\/p>\n<p>I quickly realized I was wrong.<\/p>\n<p>I didn\u2019t realise then that real strategy isn\u2019t just about planning, it\u2019s about making choices. It\u2019s about making trade-offs, aligning with business goals, and ensuring execution delivers measurable impact.<\/p>\n<p>It took hard lessons, missteps, and seeing the impact of bad strategy (or no strategy at all) to really understand what makes a data strategy effective.<\/p>\n<p>At the time, I learned this through trial and error, oh and a lot of mentoring from my CEO.<\/p>\n<p>But even today, over two decades later, I see many organizations still making the same fundamental mistakes.<\/p>\n<h4><strong>A Familiar Data Issue<\/strong><\/h4>\n<p>Many organizations today have a data strategy, but if you ask senior leadership how it contributes to business outcomes, you\u2019ll often get vague or inconsistent answers.<\/p>\n<p>The issue? Most data strategies fail to drive impact because they:<\/p>\n<ul>\n<li>Are overly focused on technology rather than business priorities.<\/li>\n<li>Lack clear alignment with revenue, cost savings, or risk mitigation.<\/li>\n<li>Are disconnected from decision-making at the executive level.<\/li>\n<li>Take too long to show tangible results, leading to loss of buy-in.<\/li>\n<\/ul>\n<h4><strong>Recognizing the Symptoms<\/strong><\/h4>\n<p>You may be facing this problem if:<\/p>\n<ul>\n<li>Your data strategy is seen as an IT initiative rather than a business enabler.<\/li>\n<li>Data \u201cprojects\u201d struggle to secure investment because their value is unclear.<\/li>\n<li>Business leaders are frustrated with slow or no progress on data initiatives.<\/li>\n<li>Teams collect and store vast amounts of data but don\u2019t translate it into real insights.<\/li>\n<li>AI and analytics investments haven\u2019t delivered the expected ROI (yet)!<\/li>\n<\/ul>\n<p>If any of this sounds familiar, you\u2019re not alone, these are common failure points in data strategy execution.<\/p>\n<h4><strong>Why This Keeps Happening<\/strong><\/h4>\n<p>These failures don\u2019t happen in isolation; they stem from recurring mistakes:<\/p>\n<ol>\n<li><strong>Strategy is confused with planning.<\/strong>\u00a0Many leaders assume that creating a strategy means laying out a multi-year roadmap. But a roadmap without clear decision-making principles isn\u2019t a strategy it\u2019s just a plan.<\/li>\n<li><strong>Technology leads the conversation.<\/strong>\u00a0Organisations invest in platforms and tools before defining the business problems they need to solve. This results in expensive solutions searching for a use case.<\/li>\n<li><strong>Data remains siloed from the business.<\/strong>\u00a0If data leaders operate separately from business strategy discussions, the connection between data and value is lost.<\/li>\n<li><strong>ROI is not front and center (how many times have I said that!) <\/strong>Data teams focus on delivery rather than impact, measuring outputs (dashboards, reports, models) rather than business outcomes (cost savings, revenue growth, efficiency gains).<\/li>\n<\/ol>\n<h4><strong>The Shift That Changes Everything<\/strong><\/h4>\n<p>Is this the \u201cAHA\u201d moment? Maybe! The actual breakthrough moment comes when organizations stop treating data strategy as an internal technical exercise and instead see it for what it is: a business strategy that uses data as a lever for growth and efficiency. That\u2019s why I\u2019ve always wished it was just called good old business strategy and that everything else was incorporated into it!<\/p>\n<p>Does it matter? Of course, it does and the shift in mindset and behaviors looks like this:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1964\" src=\"https:\/\/solutionsreview.com\/thought-leaders\/files\/2025\/02\/old-way-new-ay.webp\" alt=\"\" width=\"788\" height=\"358\" srcset=\"https:\/\/solutionsreview.com\/thought-leaders\/files\/2025\/02\/old-way-new-ay.webp 788w, https:\/\/solutionsreview.com\/thought-leaders\/files\/2025\/02\/old-way-new-ay-300x136.webp 300w, https:\/\/solutionsreview.com\/thought-leaders\/files\/2025\/02\/old-way-new-ay-768x349.webp 768w\" sizes=\"(max-width: 788px) 100vw, 788px\" \/><\/p>\n<p>This shift is where real transformation happens.<\/p>\n<p><strong>How We Make It Work<\/strong><\/p>\n<p>At datazuum, we\u2019ve seen the impact of both ineffective and effective data strategies. Here\u2019s how we ensure success:<\/p>\n<ol>\n<li><strong>Start with a business problem.<\/strong>\u00a0Instead of asking, &#8220;What\u2019s our data strategy?&#8221; we ask, &#8220;What business problem are we solving?&#8221; Whether it\u2019s customer churn, operational inefficiencies, or revenue leakage, defining the right problem is step one.<\/li>\n<li><strong>Identify high-impact use cases.<\/strong> Not all data initiatives are equally valuable. We prioritize use cases that have a direct, measurable impact on revenue, cost, or risk reduction.<\/li>\n<li><strong>Design the operating model.<\/strong>\u00a0A strategy only works if the right people, processes, and governance are in place to execute it. We establish clear roles, responsibilities, and ways of working, \u201cmaking the strategy real\u201d.<\/li>\n<li><strong>Prove value quickly.<\/strong>\u00a0Instead of waiting months for results, we focus on delivering quick wins within weeks, whether it\u2019s an insight that saves money or a pilot that unlocks new revenue.<\/li>\n<li><strong>Scale and optimize.<\/strong> Once we prove impact, we scale successful initiatives across the organization while refining processes for long-term sustainability.<\/li>\n<\/ol>\n<p><strong>What Happens When You Get It Right<\/strong><\/p>\n<p>To illustrate this approach, here are two examples of organizations that pivoted to a business-first data strategy and saw tangible results:<\/p>\n<ul>\n<li><strong>Retail: Reducing Stockouts and Overstocks<\/strong><\/li>\n<li>A global retailer struggled with inventory management, leading to lost sales due to stockouts and excess costs due to overstock. Initially, their data strategy focused on centralizing their data into a warehouse, a costly, multi-year initiative with no immediate ROI.<\/li>\n<\/ul>\n<p><strong>The shift:<\/strong>\u00a0By identifying key business use cases, starting with demand forecasting for high-value products. Using existing data more effectively, they saw a\u00a0<strong>12 percent reduction in stockouts and a 15 percent reduction in inventory holding costs within six months.<\/strong><\/p>\n<ul>\n<li><strong>Financial Services: Increasing Customer Retention<\/strong><\/li>\n<li>A bank was losing customers but lacked insight into why. Their initial approach was to build a &#8220;360-degree customer view,&#8221; an expensive project with no clear business value.<\/li>\n<\/ul>\n<p><strong>The shift:<\/strong> Focusing on high-value customer segments and identified leading indicators of churn. By deploying targeted interventions (e.g., personalized offers and proactive engagement), the bank reduced churn in priority segments by <strong>8 percent in 9 months<\/strong>, leading to\u00a0<strong>\u00a320M in retained revenue.<\/strong><\/p>\n<p><strong>What This Means for You<\/strong><\/p>\n<p>If your data strategy isn\u2019t delivering measurable results, it may be because you\u2019re treating it as a technical initiative rather than a business strategy.<\/p>\n<p>The payoff of shifting to a business-first data strategy is significant:<\/p>\n<p><strong>1. Faster, More Tangible ROI<\/strong><\/p>\n<p>Traditional data strategies take years to show impact\u2014often because they begin with foundational projects like data lakes, governance frameworks, or architecture redesigns. While these are important, they should be enablers, not the starting point.<\/p>\n<p>By focusing on targeted use cases that align with business goals, you generate value within weeks or months rather than years. This keeps leadership engaged, justifies further investment, and ensures momentum.<\/p>\n<p><strong>2. Stronger Business Buy-In and Sponsorship<\/strong><\/p>\n<p>Many data teams struggle with securing investment because they don\u2019t tie their work to business impact. A business-first strategy ensures that every data initiative has a direct link to a revenue-generating or cost-saving outcome.<\/p>\n<p>When business leaders see data as a driver of profit rather than a back-office function, they advocate for its success. This is how you move from being seen as a cost center to a value generator.<\/p>\n<p><strong>3. Love Your Data<\/strong><\/p>\n<p>Without a clear strategy, organisations accumulate vast amounts of data but fail to use it effectively or as our strapline at datazuum puts it \u201cLove Your Data\u201d. Instead of creating value, they generate complexity, technical debt, and compliance risks.<\/p>\n<p>A business-first approach ensures that data is captured, managed, and applied with purpose, turning it from an untapped resource into a driver of growth and efficiency.<\/p>\n<p><strong>4. A Future-Centric Data Function<\/strong><\/p>\n<p>By embedding data into business strategy, you ensure your data team isn\u2019t sidelined when budgets tighten or leadership changes. When your value is tied to revenue growth, cost savings, and risk management, your function is seen as essential, not optional.<\/p>\n<p><strong>Final Thought: Are You Moving in the Right Direction?<\/strong><\/p>\n<p>Many organizations spend millions on data initiatives yet struggle to prove their worth. The difference between success and failure isn\u2019t about having more data, better technology, or larger budgets, it\u2019s about embedding data into business strategy from day one. To recap follow these:<\/p>\n<ul>\n<li>Focus on business outcomes, not just data capabilities.<\/li>\n<li>Identify high-impact use cases first, rather than trying to &#8216;boil the ocean.&#8217;<\/li>\n<li>Align every data initiative with revenue generation, cost reduction, or risk mitigation.<\/li>\n<li>Demonstrate \u201cproof of value\u201d to maintain executive buy-in.<\/li>\n<\/ul>\n<p>I learned this the hard way in 2002. Many organizations are still learning it today.<\/p>\n<p>The question is will yours be one of them?<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Back in 2002, I was thrown in at the deep end, tasked with creating a data strategy for a global business I worked for. At the time, I thought &#8220;strategy&#8221; was just a sophisticated way of saying &#8220;plan.&#8221; I believed it was about mapping things out in a structured way, like a detailed blueprint. I [&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>Strategy Isn\u2019t What I Thought It Was and Many Still Get It Wrong<\/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=\"Strategy Isn\u2019t What I Thought It Was and Many Still Get It Wrong\" \/>\n<meta property=\"og:description\" content=\"Back in 2002, I was thrown in at the deep end, tasked with creating a data strategy for a global business I worked for. 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