{"id":15290,"date":"2022-01-18T00:00:00","date_gmt":"2022-01-18T00:00:00","guid":{"rendered":"https:\/\/members.dataiq.global\/articles\/the-gsk-approach-to-driving-up-data-literacy\/"},"modified":"2022-01-18T00:00:00","modified_gmt":"2022-01-18T00:00:00","slug":"the-gsk-approach-to-driving-up-data-literacy","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/the-gsk-approach-to-driving-up-data-literacy\/","title":{"rendered":"The GSK approach to driving up data literacy"},"content":{"rendered":"

Despite its prominence, the debate over data literacy\u2019s true definition rages on. David Reed\u2019s book Becoming Data Literate<\/a> <\/em>includes a helpful definition: \u201cData literacy means understanding how to create a great business with data at its heart, rather than trying to become a data business.\u201d But context is king, and the required level of literacy will inevitably vary from organisation to organisation, and from job role to job role. Indeed, the National Data Strategy<\/a>, published in October 2020, states that: \u201cWhile we do not all need to become data scientists, everyone needs some level of data literacy in order to operate successfully in increasingly data-rich environments.\u201d<\/p>\n

The need for a tailored approach is particularly true for large organisations like GSK. The pharmaceutical giant employs more than 100,000 people in a variety of business units, departments and functions. A one-size-fits-all approach could quickly become diluted in this kind of setting, and it is through this lens that GSK\u2019s chief digital and technology officer Shobie Ramakrishnan created the Data and Analytics (D&A) Accelerator team. Headed up by D&A transformation director Paul Sarjeant and D&A change lead Kelly Katerakis, the team aims to drive up data literacy across the entire organisation via its online learning platform – the GSK Data Academy.<\/p>\n

Building the Academy<\/strong><\/p>\n

Work on the Academy began in earnest in June 2020, building upon efforts that were already underway within the organisation, albeit on a dispersed basis. \u201cWork was happening in the data literacy space, but it wasn\u2019t being done at an enterprise level,\u201d said Sarjeant. \u201cShobie decided that we needed an enterprise data literacy programme out there for our GSK colleagues to participate in.\u201d<\/p>\n

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\u201cEveryone needs some level of data literacy in order to operate successfully.\u201d<\/p>\n<\/blockquote>\n

To ensure that participants received the right training, the team established three distinct personas for data literacy: Experts, Users and Consumers. Simply put, Experts are data and analytics professionals, and Users are those out in the business translating insights through user-led tools. Consumers are those being fed data-driven insights, including senior leadership, as Sarjeant explained: \u201cWe want our leaders to be data-driven in their approach, and we also need our colleagues who aren\u2019t using complex data tools every day to be able to make data-driven decisions.\u201d<\/p>\n

Each persona contains a distinct set of criteria against which staff can benchmark their skills. To do so, the change team conducted a \u201cdata state of the nation\u201d exercise. Katerakis explained: \u201cWe were able to reach 40,000 GSK colleagues via a quick pulse survey. From there, the team was able to determine current knowledge and skill levels and then focus on the lowest-scoring areas first.\u201d The pulse survey consisted of 10 \u201cgolden\u201d questions to assess competency and appetite for data in various roles.<\/p>\n

From there, the team developed tailored learning pathways to fit the needs of each persona. Sarjeant and Katerakis hope that by doing so, some of the pitfalls that are common of enterprise-wide training initiatives will be avoided. As Sarjeant explained: \u201cWhen you chuck a learning platform at someone, most people aren\u2019t going to know what they need to learn if they aren\u2019t guided to the right content.\u201d<\/p>\n

Raising the profile<\/strong><\/p>\n

Outlining a curriculum is one thing, getting people to engage with it is another. This is a particular challenge for GSK, given that participating in the Academy isn\u2019t mandatory. \u201cThe importance of data literacy isn\u2019t always obvious to someone if they haven\u2019t looked at it yet,\u201d said Katerakis. \u201cPart of our job is to guide individuals to their persona and then prompt their curiosity through initiatives like conferences, coffee lotteries and hackathons.\u201d\u00a0<\/p>\n

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“Most people aren\u2019t going to know what they need to learn without guidance.”<\/p>\n<\/blockquote>\n

To that end, in July 2021, Sarjeant\u2019s team launched DataUp! \u2013 a gamified, enterprise-wide training programme available to anyone in GSK interested in learning more about the role that data plays in the organisation. 2,000 people have accessed the material so far, wherein participants enter the \u201cuniverse\u201d of data, visiting planets to experience data use cases, take part in data-focused quizzes and earn reward badges along their way to becoming a \u201cdata superhero.\u201d Katerakis added: \u201cThis initiative translated the power of data in an approachable, digestible and fun way.\u201d<\/p>\n

Early evidence suggests that these efforts are paying off: 20,000 of GSK\u2019s 100,000 employees have interacted with Academy content since launch, but it remains a work in progress. \u201cEverything we have done has been with an agile mindset,\u201d explained Sarjeant. \u201cWe have a backlog of ideas and content generated by our users, and we provide mechanisms to trial content and generate feedback along the way.\u201d<\/p>\n

Words of advice<\/strong><\/p>\n

Bespoke initiatives like the DataUp! game will be a pipedream for most organisations, but Katerakis and Sarjeant have some advice that can be applied as a general rule for anyone embarking on a similar journey. \u201cPerseverance is key \u2013 don\u2019t be afraid to fail and try again,\u201d said Katerakis.\u00a0<\/p>\n

Meanwhile, Sarjeant believes that engaging with senior leaders is vital. \u201cExecutive sponsorship is essential, both for encouraging teams to engage with your content and then for guiding them through it,\u201d he said. \u201cThere\u2019s so much free content out there nowadays that people could upskill themselves if they wanted to, but you really need structured focus and leadership to help drive interaction.\u201d<\/p>\n

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“Don\u2019t be afraid to fail and try again.”<\/p>\n<\/blockquote>\n

It also doesn\u2019t hurt to make a bit of noise, as Katerakis explained. \u201cYou can\u2019t talk about what you\u2019re doing enough. It might feel like you\u2019re repeating yourself over-and-over again, but you have to bang that drum if you\u2019re going to get people on board.\u201d\u00a0<\/p>\n

GSK will continue to amplify its data literacy programme throughout 2022 by focusing on senior leaders and by encouraging its data experts to share use cases with the wider organisation. The ideal approach will vary from organisation to organisation, and from job role to job role, but there are universal principles at play when it comes to driving-up data literacy in any environment: make it relevant, make it accessible and make it exciting.<\/p>\n","protected":false},"excerpt":{"rendered":"

GSK\u2019s Paul Sarjeant and Kelly Katerakis outline the story behind the establishment of GSK\u2019s Data Academy – an organisation-wide initiative to drive up data literacy.<\/p>\n","protected":false},"author":17,"featured_media":15291,"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":[467,119,87,787,318],"pillar":[],"class_list":["post-15290","article","type-article","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-public","tag-culture","tag-data-literacy","tag-leadership","tag-stakeholder-engagement","tag-training"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 02:27:54","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\/15290","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\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=15290"}],"version-history":[{"count":0,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/15290\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/15291"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=15290"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=15290"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=15290"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=15290"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}