{"id":7336,"date":"2023-11-22T14:00:10","date_gmt":"2023-11-22T14:00:10","guid":{"rendered":"https:\/\/members.dataiq.global\/?post_type=article&p=7336"},"modified":"2024-03-21T10:52:47","modified_gmt":"2024-03-21T10:52:47","slug":"talent-to-achieve-data-strategy","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/talent-to-achieve-data-strategy\/","title":{"rendered":"Acquiring the data talent needed to achieve your data strategy"},"content":{"rendered":"

A robust data strategy is integral to any organisation\u2019s success today. Only by educating workforces in data analysis can businesses capitalise on the transformative insights that are now available to them.<\/span>\u00a0<\/span><\/p>\n

In f<\/span>act, a\u00a0McKinsey survey\u00a0s<\/span>uggests that organisations that heavily use customer analytics\u00a0<\/span>are\u00a0<\/span>23 times more likely to outperform their competitors that\u00a0don\u2019t\u00a0in terms of\u00a0acquiring\u00a0new customers.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Take Starbucks, for example. The\u00a0<\/span>brand uses data<\/span><\/a>\u00a0in many intelligent ways to personalise the customer experience, optimise supply chain processes and use location-based data analysis to\u00a0determine\u00a0which areas are likely to result in profitable new stores.<\/span>\u00a0<\/span><\/p>\n

The company\u2019s earnest data strategy has enabled Starbucks to become a global brand boasting 90 million transactions per week,\u00a0<\/span>with around 28% of its US orders coming from Starbucks app<\/span><\/a>.<\/span><\/p>\n

 <\/p>\n

Why data skills are key to a solid data strategy<\/span>\u00a0<\/span><\/strong><\/h4>\n

Having a team that possesses the right data skills can help any organisation flourish, not just international brands like Starbucks.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

But first things first, why is a solid data strategy essential?<\/span>\u00a0<\/span><\/p>\n

Effective data strategy is crucial to most organisation\u2019s success in a few key areas:<\/span><\/p>\n

    \n
  1. Data governance:<\/span>\u00a0Ensuring the quality of data and compliance with regulatory standards, such as GDPR.<\/span><\/li>\n
  2. Data integration:\u00a0Simplifying the process of combining data from various sources into a single, unified view. This approach reduces inefficiencies caused by having siloed data scattered across different systems.<\/span><\/li>\n
  3. Data utilisation:\u00a0Employing data to generate actionable insights that are in line with business objectives, leading to substantial business impacts.<\/span><\/li>\n<\/ol>\n

    <\/h4>\n

    Top\u00a0three\u00a0challenges of a CDO<\/span>\u00a0<\/span><\/strong><\/h4>\n

    Chief\u00a0data\u00a0officers aiming to execute their data strategies are increasingly recognising the urgent need for relevant data skills within their organisations.\u00a0<\/span>\u00a0<\/span><\/p>\n

    A 2022\u00a0Deloitte survey\u00a0h<\/span>ighlights what CDOs regard as their top three challenges when it comes to their data strategies:<\/span><\/p>\n

      \n
    1. Communicating effectively with the executive committee<\/strong>\u00a0\u2013<\/span>\u00a0<\/span>CDOs often struggle to successfully communicate useful insights in terms non-data professionals can easily understand. This hinders data\u2019s influence on decision making within their organisations.<\/span><\/li>\n
    2. Limited data skills<\/strong>\u00a0\u2013\u00a0<\/span>CDOs report that their teams lack the adequate skills to transform data into actionable insights for their businesses.<\/span><\/li>\n
    3. Constrained by data literacy<\/strong>\u00a0\u2013<\/span>\u00a0CDOs report that their teams are not able to read, write and understand data.<\/span>\u00a0<\/span><\/li>\n<\/ol>\n
      \"Three
      Three pie charts examining the top challenges of CDOs.<\/figcaption><\/figure>\n

      How to\u00a0acquire\u00a0the right data talent to overcome CDO challenges<\/span>\u00a0<\/span><\/strong><\/h4>\n

      Recruiting new employees into a business is often seen as a painless method to bridge the data skills gap in an organisation. However, approaches such as\u00a0<\/span>using specialist recruiting agencies<\/span><\/a>\u00a0can come with significant expenses and hidden costs too.<\/span>\u00a0<\/span><\/p>\n

      As of December 2022, data from the Office for National Statistics estimates the average annual salary for full-time workers in Great Britain is \u00a332,760. And\u00a0<\/span>recruitment agencies typically charge<\/span><\/a>\u00a0between 10% and 30% of the employee\u2019s\u00a0initial\u00a0salary, leading to costs ranging from \u00a33,276 to \u00a39,828 per new hire.<\/span>\u00a0<\/span><\/p>\n

      Moreover, the risk of new hires not lasting long enough to realise a return on this investment is\u00a0substantial. Nearly\u00a0<\/span>50% of new employees<\/span><\/a>\u00a0do not succeed\u00a0beyond the first 18 months of employment.<\/span>\u00a0<\/span><\/p>\n

      According to a report by the Society for Human Resource Management (SHRM),\u00a0the\u00a0<\/span>cost of replacing a salaried employee<\/span><\/a>\u00a0can amount to 6 to 9 months of their salary.\u00a0<\/span>\u00a0<\/span><\/p>\n

      So how can you\u00a0acquire\u00a0the right data talent for your team without these\u00a0additional\u00a0costs?<\/span>\u00a0<\/span><\/p>\n

      \u00a0<\/span><\/p>\n

      Upskilling with data apprenticeships<\/span>\u00a0<\/span><\/strong><\/h4>\n

      Organisations are increasingly recognising the value of enhancing the skills of their current workforce with\u00a0<\/span>apprenticeship programmes<\/span><\/a>\u00a0as a cost-effective alternative to hiring\u00a0new staff.\u00a0<\/span>\u00a0<\/span><\/p>\n

      This trend is\u00a0evident\u00a0in the findings of the IBM Institute for Business Value\u2019s “<\/span>2023 Chief Data Officer Study: Turning data into value<\/span><\/a>,” which surveyed 3,000 CDOs.\u00a0<\/span>\u00a0<\/span><\/p>\n

      Among these, 8% were classified as\u00a0value\u00a0creator CDOs, who, despite lower spending on data strategy and management, reported equal or higher annual revenue growth than their counterparts.\u00a0<\/span>\u00a0<\/span><\/p>\n

      Most importantly, these CDOs attributed their success to several key actions, including expanded training and reskilling initiatives to boost data literacy within their organisations.<\/span>\u00a0<\/span><\/p>\n

      Upskilling with data analyst apprenticeships, in particular, offers\u00a0several benefits:<\/span><\/p>\n

        \n
      1. Boosting productivity:\u00a0<\/span>Upskilling in data-related areas has been shown to enhance workplace productivity. In fact, according to a<\/span>\u00a0Talent LMS survey<\/span><\/a>,\u00a0<\/span>91% of companies and 81% of employees say upskilling or reskilling training has boosted productivity at work.<\/span><\/li>\n
      2. Enabling hub-and-spoke models:\u00a0By training employees from various departments in data literacy and analytics skills, organisations can ease the strain on their advanced data teams, allowing them to focus on more complex tasks and become value drivers.<\/span><\/li>\n
      3. Adapting to evolving technologies:\u00a0A 2023 McKinsey report h<\/span>ighlights the transformative potential of generative AI technologies in data analytics and other sectors. Upskilling is crucial to keep pace with these technological advancements.<\/span><\/li>\n
      4. Maintaining competitive advantage:\u00a0A<\/span>\u00a0Deloitte report u<\/span>nderscores the ongoing high demand for data analytics professionals, emphasising the importance of upskilling to meet this demand and maintain a competitive edge.<\/span><\/li>\n
      5. Retaining top talent:\u00a0Investing in upskilling not only benefits employees but also contributes positively to a company\u2019s bottom line by improving employee retention, productivity, and profitability.<\/span>\u00a0<\/span><\/li>\n<\/ol>\n

         <\/p>\n

        CDOs looking to future-proof their data strategy should consider the potential of upskilling and reskilling their existing workforce.\u00a0<\/span>\u00a0<\/span><\/p>\n

        \u00a0<\/span><\/p>\n

        Funding through the UK Apprenticeship Levy<\/span>\u00a0<\/span><\/strong><\/h4>\n

        At this point, you may be wondering how much these upskilling programmes will cost and how you\u2019ll ever get budget approval? Well, the following bit might surprise you.<\/span>\u00a0<\/span><\/p>\n

        If your organisation pays into the UK Apprenticeship Levy, there is actually no additional cost for your organisation to use these apprenticeships for upskilling.<\/span><\/p>\n

        The UK Apprenticeship Levy is a tax-funded levy first introduced in April 2017 and is aimed at funding apprenticeship programmes across the country. It requires all employers with an annual pay bill over \u00a33 million to contribute 0.5% of their total pay bill to the levy.\u00a0<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

        This contribution is ring-fenced and accessible only to finance apprenticeship training.\u00a0<\/span>\u00a0<\/span><\/p>\n

        \u00a0<\/span>\u00a0<\/span><\/p>\n

        What if your organisation\u00a0doesn\u2019t\u00a0pay into the Levy?\u00a0<\/span>\u00a0<\/span><\/strong><\/h4>\n

        Companies with yearly payrolls below \u00a33 million, which are exempt from contributing to the levy, are still eligible for government-supported apprenticeship schemes for their employees.\u00a0<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

        The UK government commits to funding 95% of apprenticeship programmes\u2019 costs. As a result, your organisation will only be required to invest a maximum of 5% towards the overall cost of an apprenticeship, extending greater access to upskilling to smaller organisations.<\/span>\u00a0<\/span><\/p>\n

        \u00a0<\/span><\/p>\n

        Conclusion<\/span><\/strong>\u00a0<\/span><\/h4>\n

        Despite the hurdles of inadequate data literacy and skill shortages, data apprenticeships present a practical and affordable approach to building effective data teams within organisations.<\/span><\/p>\n

        Apprenticeships reduce the risks linked to recruiting external personnel and help promote a culture that values data. For CDOs aiming to secure their data strategies for the future, data apprenticeships are an essential resource.<\/span><\/p>\n

         <\/p>\n

        Are you looking to upskill your workforce so your organisation can excel in the age of data and AI? Get in touch with\u00a0Cambridge Spark<\/a>\u00a0and\u00a0transform the way your teams work with data together.\u00a0<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

        CDOs need to educate teams across an organisation and ensure a robust data strategy is in place to capitalise on the transformative insights available.<\/p>\n","protected":false},"author":19,"featured_media":7337,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,131],"tags":[363,361,119,123,364,362,304],"pillar":[195,193],"class_list":["post-7336","article","type-article","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-member-articles","tag-apprenticeship","tag-cambridge-spark","tag-data-literacy","tag-data-strategy","tag-levy","tag-transformation","tag-upskilling","pillar-literacy","pillar-strategy"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 04:24:58","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\/7336","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=7336"}],"version-history":[{"count":0,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/7336\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/7337"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=7336"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=7336"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=7336"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=7336"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}