{"id":41073,"date":"2026-02-11T11:36:14","date_gmt":"2026-02-11T11:36:14","guid":{"rendered":"https:\/\/www.dataiq.global\/?post_type=article&#038;p=41073"},"modified":"2026-02-11T16:56:26","modified_gmt":"2026-02-11T16:56:26","slug":"making-data-products-stick","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/making-data-products-stick\/","title":{"rendered":"Making Data Products Stick: Driving Adoption, Speed and Value in Mature Organisations"},"content":{"rendered":"<p><i><span data-contrast=\"none\">DataIQ clients can find the <\/span><\/i><a href=\"https:\/\/hub.dataiq.global\/posts\/making-data-products-stick-driving-adoption-speed-and-value-in-mature-organisations\" rel=\"nofollow noopener\" target=\"_blank\"><i><span data-contrast=\"none\">full set of learnings here<\/span><\/i><\/a><i><span data-contrast=\"none\">.\u00a0<\/span><\/i><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/www.dataiq.global\/devstage\/what-dataiq-does\/\"><i><span data-contrast=\"none\">Click here<\/span><\/i><\/a><i><span data-contrast=\"none\"> to become a DataIQ client and access all the learnings, plus regular masterclass sessions and other peer-led discussions.<\/span><\/i><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3>Synopsis<\/h3>\n<p><span data-contrast=\"auto\">A large global bank is adopting a data product approach. After substantial investments in data platforms and foundational capabilities, expectations are now shifting towards demonstrable business value and faster delivery and adoption. Framing data products as a tiered ecosystem \u2013 from raw, experimental data assets through to foundational, business and enterprise-level products, this DataIQ client sought peer advice on balancing speed, democratisation and trust. <\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span data-contrast=\"auto\">Peers from mature, complex organisations shared practical lessons on accelerating adoption, embedding data products into workflows and decisions, structuring\u00a0teams\u00a0and funding models, and using speed, rather than perfection, as a strategic lever.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Client Questions<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<ul>\n<li><span data-contrast=\"auto\">What does it take to build data products that are\u00a0actually used\u00a0by the business?<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">How are teams integrating data products into real workflows, decisions, and outcomes?<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">What have we learned about the roles, structures, and habits that make these efforts succeed?<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Anchor data products to urgent business demand<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Peers consistently stressed that adoption improves when data products are built around\u00a0real business\u00a0demand, not enterprise ideals. Products gained traction when they unlocked something the business urgently needed, such as group-level visibility during an acquisition or insight that could not be delivered through existing reports.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Attempts to replace legacy pipelines that \u201cstill worked\u201d met strong resistance. By contrast, new use cases created pull rather than push. Adoption accelerates when data products remove an immediate blocker, not when they are positioned as cleaner alternatives to familiar outputs.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span data-contrast=\"auto\">Prove value early by keeping products deliberately small<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Several leaders reflected that early data products failed because they were too broad and abstract to gain traction. Momentum improved when teams aggressively narrowed scope to a small number of high-impact products and worked closely with users. Right-sized products moved faster through modelling and governance, enabled earlier feedback, and made ownership clearer\u2014shortening time-to-first-use\u00a0while foundational work continued in parallel.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Target business-embedded analysts as the primary adoption channel<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Across sectors, leaders were clear that the fastest route to adoption runs through analysts embedded in business functions, rather than central data teams or end users. These insight and analytics teams sit close to decisions, understand the context of the data, and act as an intermediary layer, using trusted data products to create dashboards,\u00a0analyses\u00a0and insights for wider audiences.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">End users rarely consume data products directly. Instead, business-embedded analysts value consistency,\u00a0speed\u00a0and semantic clarity, and\u00a0are able to\u00a0work with transparent quality constraints without waiting for perfection. By enabling these teams first through curated data products and governed semantic layers, organisations accelerate downstream value and data democratisation without over-engineering products for every user group.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Integrate data products into workflows via semantic and consumption layers<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Many organisations deliberately limit direct access to curated data products, instead embedding them into everyday workflows through semantic models and\u00a0BI layers. This approach allows analytical teams to self-serve from trusted data products while ensuring outputs are delivered through tools the business already uses, such as dashboards and reports, reducing duplication and protecting trust.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In practice, curated products are consumed via semantic models (such as those from Power BI), while direct access to the\u00a0lakehouse\u00a0is tightly controlled through persona-based entitlements and fine-grained row- and column-level policies enforced using tools. While this model accelerates adoption and supports data democratisation where it matters most, peers acknowledged ongoing tension from teams seeking deeper access to raw data, making clear personas,\u00a0boundaries\u00a0and governance essential to sustaining trust at scale.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Separate governance,\u00a0ownership\u00a0and delivery to remove bottlenecks<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Peers agreed that architect-led approaches help\u00a0establish\u00a0consistency and trust in complex, regulated environments, but stall quickly when architecture becomes detached from business ownership and delivery. One leader shared a federated operating model designed to avoid this by clearly separating governance, business\u00a0accountability\u00a0and information management.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In this model, data governance provides guardrails rather than control, with data officers embedded in business functions, supported by data custodians, and data governance managers setting standards and maturity criteria. Business owners and named data product owners are accountable for defining requirements, prioritising delivery and driving adoption, making it explicit that data products are a business responsibility, not an IT deliverable. Architectural leadership and platform teams ensure coherence and quality, while cross-functional data product teams build pipelines and prepare data up to the product boundary, enabling rapid delivery without fragmenting enterprise consistency.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This separation of responsibilities reduces bottlenecks, makes adoption someone\u2019s explicit job, and allows data products to move faster without undermining trust or governance.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Fund data products beyond the projects that create them<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Leaders highlighted a recurring failure mode: data products built for projects lacked funding once delivery ended. One organisation addressed this through graded product levels and central funding for the \u201clast mile\u201d to support products that delivered enterprise value. Without sustainable funding, data products\u00a0remain\u00a0temporary assets rather than enduring capabilities.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<h3><span data-contrast=\"auto\">Protect momentum by limiting collaboration<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">Over-collaboration surfaced as a drag on speed. Leaders warned against striving for early perfection or one-size-fits-all solutions, advocating instead for incremental delivery and visible progress. Momentum sustains sponsorship. Excessive alignment destroys it.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><em><a href=\"https:\/\/www.dataiq.global\/devstage\/what-dataiq-does\/\">Become a DataIQ client <\/a>to access the full set of learnings and many more exclusive insight pieces.\u00a0<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data product adoption across mature organisations continues to be a bottleneck, despite strong investment. DataIQ  clients came together to examine their successes. <\/p>\n","protected":false},"author":19,"featured_media":41074,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,398],"tags":[1120,1458,540,1255,1460,229,1461],"pillar":[197],"class_list":["post-41073","article","type-article","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-public","tag-adoption","tag-data-product","tag-exclusive","tag-speed","tag-uptake","tag-value","tag-workflows","pillar-technology"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 01:43:26","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/41073","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=41073"}],"version-history":[{"count":3,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/41073\/revisions"}],"predecessor-version":[{"id":41091,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/41073\/revisions\/41091"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/41074"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=41073"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=41073"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=41073"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=41073"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}