{"id":1107,"date":"2020-06-29T14:53:25","date_gmt":"2020-06-29T14:53:25","guid":{"rendered":"http:\/\/janbosch.com\/blog\/?p=1107"},"modified":"2020-06-29T14:53:27","modified_gmt":"2020-06-29T14:53:27","slug":"exploiting-your-data-well","status":"publish","type":"post","link":"https:\/\/janbosch.com\/blog\/index.php\/2020\/06\/29\/exploiting-your-data-well\/","title":{"rendered":"Exploiting your data well"},"content":{"rendered":"\n
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Image by Gerd Altmann from Pixabay\n<\/figcaption><\/figure>\n\n\n\n

Based on our research, we\u2019ve developed a four-dimensional model for the digital transformation in the software-intensive embedded systems industry. In the last two posts, we explored the business model<\/a> and product upgr<\/a>ade <\/a>dimensions. This post is concerned with the data exploitation dimension.<\/p>\n\n\n\n

As shown in the figure, the first step in most companies is focused \non the use of data for quality assurance and diagnostics. In this case, \nthe data often arrives at the company in batches and through customer \ncomplaints. In response to a complaint, company representatives download\n the data and investigate whether the system behaved incorrectly and \nseek to identify the root cause. Many companies have been using this \ntype of data for decades.<\/p>\n\n\n\n

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Evolving use of data<\/figcaption><\/figure>\n\n\n\n

The second step is the use of data to monitor product performance and\n feature usage. This form of data collection is typically introduced in \ncombination with the more frequent deployment of software. Monitoring \nproduct performance allows the company to confirm that the product is \nperforming well after a software upgrade. Measuring feature usage allows\n for more informed prioritization of R&D resources by ensuring that \nresearch and development predominantly focus on improving features that \nare actually used by customers.<\/p>\n\n\n\n

As we now have a continuous stream of data from each customer, we can\n move to the third stage where we can start to collect data relevant for\n the customer. Each customer has KPIs for which the organization \noptimizes, including churn in subscription service companies, measuring \nservice usage by end-customers or classifying end-customers into \nsegments that require different treatments. As the company now collects \nsignificant amounts of data from each customer, it can process and \nanalyze that data and offer relevant insights to each customer. advertorial \n\n<\/p>\n\n\n\n

In the third stage, we only use the data from one customer for that \ncustomer (typically for legal reasons), but the logical next step is to \naggregate data from all customers and to provide relevant comparative \ndata to each customer. At this point, the company can offer each \ncustomer an assessment of their business in how it compares to other, \nsimilar companies. This allows each customer to identify where they\u2019re \nahead of the competition, where they\u2019re on par and where they\u2019re behind.\n That facilitates the prioritization of improvement efforts at \ncustomers, which is very valuable for most of them.<\/p>\n\n\n\n

Finally, in the last stage, the company engages a second business \necosystem where it monetizes data collected from its primary customer \nbase with a secondary customer base. For instance, a truck company could\n sell route information of the trucks in use at its customers to gas \nstation and road service companies. Or, a telecom company could sell \naggregate movement patterns of mobile phone users to city planners.<\/p>\n\n\n\n

Once the company reaches the final stage, the data that\u2019s collected \nin its products deployed at its primary customer base now is \nincreasingly concerned with meeting the needs of the secondary customer \nbase. So, the company is likely to start collecting data that has no \nrelevance at all for its primary customer base but that is relevant for \nthe secondary one. A second aspect is that the company can use the \nrevenue from the secondary customer base to subsidize the products to \nits primary customer base and, through that, grow its market share. Many\n industries, as digitalization takes hold, move towards a \u201cwinner takes \nall\u201d situation and this pattern of positive feedback cycles lies at the \nroot of it.<\/p>\n\n\n\n

Concluding, digitalization has implications for the business model, the way we upgrade products and the way that we collect, use and monetize data. Companies evolve in predictable and repeatable patterns through this transformation and in this post, I described the five typical stages we encounter in our research. Data is the new oil, but if you\u2019re not able to generate business value from your data, it doesn\u2019t do you much good. So, get going on experimenting with different ways to create value from your data!<\/p>\n\n\n\n

To get more insights earlier, sign up for my newsletter at <\/em>jan@janbosch.com<\/em><\/a> or follow me on<\/em> janbosch.com\/blog<\/em><\/a>, LinkedIn (<\/em>linkedin.com\/in\/janbosch<\/em><\/a>) or Twitter (<\/em>@JanBosch<\/em><\/a>).<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Based on our research, we\u2019ve developed a four-dimensional model for the digital transformation in the software-intensive embedded systems industry. In the last two posts, we explored the business model and product upgrade dimensions. This post is concerned with the data exploitation dimension. As shown in the figure, the first step in most companies is focused … 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":[4,10],"tags":[],"_links":{"self":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1107"}],"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=1107"}],"version-history":[{"count":1,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1107\/revisions"}],"predecessor-version":[{"id":1109,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1107\/revisions\/1109"}],"wp:attachment":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1107"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1107"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1107"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}