{"id":1157,"date":"2020-11-06T13:25:30","date_gmt":"2020-11-06T13:25:30","guid":{"rendered":"http:\/\/janbosch.com\/blog\/?p=1157"},"modified":"2020-11-06T13:25:31","modified_gmt":"2020-11-06T13:25:31","slug":"making-data-driven-real","status":"publish","type":"post","link":"https:\/\/janbosch.com\/blog\/index.php\/2020\/11\/06\/making-data-driven-real\/","title":{"rendered":"Making data-driven real"},"content":{"rendered":"\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" src=\"https:\/\/janbosch.com\/blog\/wp-content\/uploads\/2020\/11\/franki-chamaki-1K6IQsQbizI-unsplash-1024x768.jpg\" alt=\"\" class=\"wp-image-1158\" srcset=\"https:\/\/janbosch.com\/blog\/wp-content\/uploads\/2020\/11\/franki-chamaki-1K6IQsQbizI-unsplash-1024x768.jpg 1024w, https:\/\/janbosch.com\/blog\/wp-content\/uploads\/2020\/11\/franki-chamaki-1K6IQsQbizI-unsplash-300x225.jpg 300w, https:\/\/janbosch.com\/blog\/wp-content\/uploads\/2020\/11\/franki-chamaki-1K6IQsQbizI-unsplash-768x576.jpg 768w, https:\/\/janbosch.com\/blog\/wp-content\/uploads\/2020\/11\/franki-chamaki-1K6IQsQbizI-unsplash.jpg 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption>Photo by Franki Chamaki on Unsplash<\/figcaption><\/figure>\n\n\n\n<p>Recently, I expert-facilitated a workshop at a company having the  desire to become data driven. Different from the product companies that I  normally work with, this company is a service provider with a large  amount of staff offering services to customers. The workshop  participants included the CEO and head of business development, as well  as several others that are in or close to the company\u2019s leadership team.<\/p>\n\n\n\n<p>In many ways, this looks to be the ideal setup as one would assume \nthat we have all the management support we need and some of the smartest\n people in the company with us. This was even reinforced by several in \nthe company sharing that they\u2019ve been working with data for quite a long\n time. Nevertheless, we ran into a significant set of challenges and we \ndidn\u2019t nearly get as far as we\u2019d hoped.<\/p>\n\n\n\n<p>The first challenge was becoming concrete on specific hypotheses to \ntest. Even though we shared concrete examples of hypotheses and \nassociated experiments when we kicked off the brainstorming and \nteamwork, everyone was having an incredibly hard time to go from a \nhigh-level goal of increasing a specific business KPI, eg customer \nsatisfaction, to a specific hypothesis and an associated concrete \nexperiment. There are many reasons for this. An obvious one is that many\n people feel that \u2018someone\u2019 should \u2018do something\u2019 about the thing that \nthey worry about but never spend many brain cycles thinking about what \nthat would look like.<\/p>\n\n\n\n<p>The second challenge was that, for all the data the company had at \nits disposal, the data relevant in the situation at hand was frequently \nunavailable. Many companies I work with claim to have lots of data and \nmany in the organization get really surprised that \u2018just\u2019 the data they \nneed hasn\u2019t been recorded. When you reflect on it, it\u2019s obvious that \nthis would be the case as the number of hypotheses that one can \nformulate is virtually infinite and, consequently, the likelihood of \ndata not being available is quite significant.<\/p>\n\n\n\n<p>The third challenge we ran into was that even in the cases where the \ndata was available, it turned out to be aggregated and\/or have a too low\n frequency of recording to be relevant for the purpose at hand. So, we \nhave the data, but it\u2019s in a form that doesn\u2019t allow for the analysis \nthat we want to do.<\/p>\n\n\n\n<p>The response to these challenges is, as one would expect, to go out \nand collect what we need to pursue the experiment to get to a \nconfirmation or rejection of the hypothesis. The funny realization that I\n had is that the more relevant and important the hypothesis is from a \nbusiness perspective, the more likely it relates to regulatory \nconstraints that limit what can be collected without going through a \nhost of disclaimers and permissions. So, we ran into the situation that \nseveral of the more promising hypotheses were not testable due to legal \nconstraints.<\/p>\n\n\n\n<p>Finally, even if we had a specific hypothesis and associated \nexperiment and we were able to collect the data we needed, it proved \nincredibly hard to scale to the point of statistical significance. \nRunning a large-scale experiment that has a decent chance of failure, \nbut that\u2019s very expensive and risky to run kind of defeats the purpose \nof experimentation.<\/p>\n\n\n\n<p>Becoming a data-driven organization is one of the highest-priority  goals that any company should have. It allows for much higher-quality  decision-making and operations while preparing for use of AI as a key  differentiator and enabler. However, going from word to action is a  challenging journey where, ideally, you learn from other people\u2019s  mistakes before making new ones yourself. We need the data, but we need  to be smart in execution.<\/p>\n\n\n\n<p><em>To get more insights earlier, sign up for my newsletter at&nbsp;<\/em><a rel=\"noreferrer noopener\" href=\"https:\/\/mailto:jan@janbosch.com\/\" target=\"_blank\"><em>jan@janbosch.com<\/em><\/a><em> or follow me on<\/em><a rel=\"noreferrer noopener\" href=\"https:\/\/janbosch.com\/blog\" target=\"_blank\"> <em>janbosch.com\/blog<\/em><\/a><em>, LinkedIn (<\/em><a rel=\"noreferrer noopener\" href=\"https:\/\/www.linkedin.com\/in\/janbosch\/\" target=\"_blank\"><em>linkedin.com\/in\/janbosch<\/em><\/a><em>) or Twitter (<\/em><a rel=\"noreferrer noopener\" href=\"https:\/\/twitter.com\/JanBosch\" target=\"_blank\"><em>@JanBosch<\/em><\/a><em>).<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Recently, I expert-facilitated a workshop at a company having the desire to become data driven. Different from the product companies that I normally work with, this company is a service provider with a large amount of staff offering services to customers. The workshop participants included the CEO and head of business development, as well as &#8230; <a title=\"Making data-driven real\" class=\"read-more\" href=\"https:\/\/janbosch.com\/blog\/index.php\/2020\/11\/06\/making-data-driven-real\/\" aria-label=\"Read more about Making data-driven real\">Read more<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"generate_page_header":"","footnotes":""},"categories":[4,8],"tags":[],"_links":{"self":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1157"}],"collection":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=1157"}],"version-history":[{"count":1,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1157\/revisions"}],"predecessor-version":[{"id":1159,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1157\/revisions\/1159"}],"wp:attachment":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1157"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1157"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1157"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}