{"id":527,"date":"2024-01-01T14:51:27","date_gmt":"2024-01-01T14:51:27","guid":{"rendered":"https:\/\/solutionsreview.com\/expert\/?p=527"},"modified":"2024-02-02T14:40:50","modified_gmt":"2024-02-02T14:40:50","slug":"two-key-questions-in-designing-monetizable-data-products","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/","title":{"rendered":"Two Key Questions In Designing Monetizable Data Products"},"content":{"rendered":"<p style=\"text-align: justify;\">The three main purposes of data in business are to enable improved operations, compliance and decision-making. Research by McKinsey Consulting <a class=\"color-link external\" title=\"https:\/\/www.mckinsey.com\/business-functions\/growth-marketing-and-sales\/our-insights\/insights-to-impact-creating-and-sustaining-data-driven-commercial-growth\" href=\"https:\/\/www.mckinsey.com\/business-functions\/growth-marketing-and-sales\/our-insights\/insights-to-impact-creating-and-sustaining-data-driven-commercial-growth\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:https:\/\/www.mckinsey.com\/business-functions\/growth-marketing-and-sales\/our-insights\/insights-to-impact-creating-and-sustaining-data-driven-commercial-growth\" aria-label=\"found\">found<\/a>\u00a0that data-driven companies report that growth and earnings before interest, taxes, depreciation and amortization (EBITDA) increase by up to 25%.<\/p>\n<p style=\"text-align: justify;\">As I&#8217;ve\u00a0<a class=\"color-link external\" title=\"https:\/\/www.forbes.com\/sites\/forbestechcouncil\/2022\/04\/15\/the-5cs-for-building-monetizable-data-products\/?sh=65e083e1126f\" href=\"https:\/\/www.forbes.com\/sites\/forbestechcouncil\/2022\/04\/15\/the-5cs-for-building-monetizable-data-products\/?sh=65e083e1126f\" target=\"_self\" rel=\"noopener nofollow\" data-ga-track=\"InternalLink:https:\/\/www.forbes.com\/sites\/forbestechcouncil\/2022\/04\/15\/the-5cs-for-building-monetizable-data-products\/?sh=65e083e1126f\" aria-label=\"previously mentioned\">previously mentioned<\/a>, data products\u2014the results of data and analytics activity to assist in the creation of new revenue sources as well as to lower both expenses and risk\u2014are crucial for improving business results. Against this backdrop, many companies today are looking at ways to leverage data for improved business results using data products.<\/p>\n<p style=\"text-align: justify;\">Almost every data-abundant company today is exploring options to build a monetizable data product, but many of them have challenges on where and how to start when it comes to design. Specifically, two key questions are associated with designing monetizable data products.<\/p>\n<p style=\"text-align: justify;\"><strong>1. Who are the potential consumers of the data product?<\/strong><\/p>\n<p style=\"text-align: justify;\">At the highest level, information in the data product can be of three main types: raw data, aggregated data and insights. Building the data product involves the level of information that needs to be shared with the target customers. The target market for data can be the firm&#8217;s internal employees or even external stakeholders, which include customers, vendors, regulators, partners and competitors.<\/p>\n<p style=\"text-align: justify;\">Identifying the potential consumers for the data products can be done with value-stream mapping (VSM). VSM is a sequence of steps regarding how the company&#8217;s product or service reaches the final customer. In VSM, the focus is on finding those activities and the associated data that add value to the customer. As data cuts across the entire VSM (both forward and backward), VSM can help identify specific data required by the potential customer.<\/p>\n<p style=\"text-align: justify;\"><strong>2. What are the compliance requirements associated with data?<\/strong><\/p>\n<p style=\"text-align: justify;\">The second design factor in the design of data products pertains to data compliance. An average company takes large amounts of time and effort to harness data. Can the firm afford to easily give away that data? Data is increasingly seen as the moat (i.e., the competitive advantage the company can hold against other businesses). In this backdrop, data compliance ensures that the critical data of the company is protected so as to maintain the firm&#8217;s competitive advantage, including satisfying the regulatory compliance. For example, if the product profit margin data is shared with the vendors as a data product, it might jeopardize the competitive advantage of the firm. Data compliance also includes adherence to the regulations that the organization must follow on how to manage its entire data life cycle. For example, sharing privacy data may adversely affect the legal compliance requirements defined in HIPAA, GDPR, CCPA and more.<\/p>\n<p style=\"text-align: justify;\">What can a company do to address data compliance? What design elements are associated with data compliance? Managing data compliance requirements is tied to the company&#8217;s data strategy\u2014the process of managing data to serve the business objectives. There are\u00a0<a class=\"color-link external\" title=\"https:\/\/hbr.org\/2017\/05\/whats-your-data-strategy\" href=\"https:\/\/hbr.org\/2017\/05\/whats-your-data-strategy\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:https:\/\/hbr.org\/2017\/05\/whats-your-data-strategy\" aria-label=\"two main types\">two main types<\/a>\u00a0of data strategies: offensive and defensive. Offensive data strategies focus on getting value out of data to improve the firm&#8217;s competitive position, reduce margins, improve profitability and so on. Defensive strategies focus more on risk mitigation, operations and regulatory compliance, to name a few.<\/p>\n<p style=\"text-align: justify;\">In terms of the three main types of information discussed earlier, an offensive data strategy focuses more on insights, while a defensive strategy focuses on data. Fundamentally, offensive and defensive data strategies are mutually exclusive and help with the selection of the right data strategy based on the industry type. Companies in the oil and gas, mining, and healthcare industries\u2014which focus more on regulations\u2014need raw data and aggregated data in the data products, while companies in the retail, consumer packaged goods and media industries focus more on aggregated data and insights in their data products.<\/p>\n<p style=\"text-align: justify;\">According to a McKinsey\u00a0<a class=\"color-link external\" title=\"https:\/\/www.mckinsey.com\/business-functions\/quantumblack\/our-insights\/how-to-unlock-the-full-value-of-data-manage-it-like-a-product\" href=\"https:\/\/www.mckinsey.com\/business-functions\/quantumblack\/our-insights\/how-to-unlock-the-full-value-of-data-manage-it-like-a-product\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:https:\/\/www.mckinsey.com\/business-functions\/quantumblack\/our-insights\/how-to-unlock-the-full-value-of-data-manage-it-like-a-product\" aria-label=\"report\">report<\/a>: &#8220;Creating reusable data products and patterns&#8230; enables companies to derive value from data.&#8221;<strong><em>\u00a0<\/em><\/strong>Finding the answers to these key questions can help organizations design data products for building a monetizable data product.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The three main purposes of data in business are to enable improved operations, compliance and decision-making. Research by McKinsey Consulting found\u00a0that data-driven companies report that growth and earnings before interest, taxes, depreciation and amortization (EBITDA) increase by up to 25%. As I&#8217;ve\u00a0previously mentioned, data products\u2014the results of data and analytics activity to assist in the [&hellip;]<\/p>\n","protected":false},"author":432,"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>Two Key Questions In Designing Monetizable Data Products<\/title>\n<meta name=\"description\" content=\"Prashanth Southekal reviews two important questions about designing monetizable data products and shares his thoughts.\" \/>\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=\"Two Key Questions In Designing Monetizable Data Products\" \/>\n<meta property=\"og:description\" content=\"Prashanth Southekal reviews two important questions about designing monetizable data products and shares his thoughts.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/\" \/>\n<meta property=\"og:site_name\" content=\"Solutions Review Thought Leaders\" \/>\n<meta property=\"article:published_time\" content=\"2024-01-01T14:51:27+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-02-02T14:40:50+00:00\" \/>\n<meta name=\"author\" content=\"Prashanth Southekal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Prashanth Southekal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/\",\"url\":\"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/\",\"name\":\"Two Key Questions In Designing Monetizable Data Products\",\"isPartOf\":{\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/#website\"},\"datePublished\":\"2024-01-01T14:51:27+00:00\",\"dateModified\":\"2024-02-02T14:40:50+00:00\",\"author\":{\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/#\/schema\/person\/ecca132a165bddd87f1c093e77981b70\"},\"description\":\"Prashanth Southekal reviews two important questions about designing monetizable data products and shares his thoughts.\",\"breadcrumb\":{\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/two-key-questions-in-designing-monetizable-data-products\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/solutionsreview.com\/thought-leaders\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Two Key Questions In Designing Monetizable Data Products\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/#website\",\"url\":\"https:\/\/solutionsreview.com\/thought-leaders\/\",\"name\":\"Solutions Review Thought Leaders\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/solutionsreview.com\/thought-leaders\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/#\/schema\/person\/ecca132a165bddd87f1c093e77981b70\",\"name\":\"Prashanth Southekal\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/solutionsreview.com\/thought-leaders\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/47cc283c07825713f7f9d9dc91d653e3?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/47cc283c07825713f7f9d9dc91d653e3?s=96&d=mm&r=g\",\"caption\":\"Prashanth Southekal\"},\"description\":\"Prashanth Southekal is the Managing Principal of DBP-Institute, a data and analytics consulting and education firm. 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