{"id":1147,"date":"2020-10-13T07:41:09","date_gmt":"2020-10-13T07:41:09","guid":{"rendered":"http:\/\/janbosch.com\/blog\/?p=1147"},"modified":"2020-10-13T07:41:15","modified_gmt":"2020-10-13T07:41:15","slug":"make-money-from-data","status":"publish","type":"post","link":"https:\/\/janbosch.com\/blog\/index.php\/2020\/10\/13\/make-money-from-data\/","title":{"rendered":"Make money from data"},"content":{"rendered":"\n
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Image by Kevin Schneider from Pixabay\n<\/figcaption><\/figure>\n\n\n\n

There\u2019s an interesting development going on in the embedded-systems industry. Initially, data was only used for internal purposes and quality assurance. Customers would send log files to product companies who would analyze them to figure out why the product wasn\u2019t operating as it should and what to do about it. Over time, the periodic data sets have turned into more or less continuous data streams and the data collected has evolved from being concerned with QA to focusing on product performance and measuring value delivery to customers.<\/p>\n\n\n\n

As the volume and expenses associated with collecting and storing \ndata have increased, companies have been investigating ways to create \nnovel value from this data through direct or indirect monetization. We \ncan identify at least four phases that companies go through.<\/p>\n\n\n\n

The first step is where the company gives the data away as part of \nthe overall product offering. Typically, the data is processed and \nprovides nice dashboards for customers to gain an understanding of the \nproduct\u2019s performance. However, as the customer gets this for free, \nthere\u2019s limited focus on the data part of the total offering. This is \nsimilar to how, in many industries, software was given away for free as \npart of the mechanical or electronic product. We\u2019re now getting paid for\n software, but many are now giving data away for free.<\/p>\n\n\n\n

The second step is where the company has developed some form of \ndata-driven service to customers using the data from each specific \ncustomer. Here, the first monetization of the data starts and even if it\n often is a minor revenue stream, both customers and the company itself \nare now, in fact, benefiting from the collected data.<\/p>\n\n\n\n

Once the second step is in place, often customers ask the company how\n they perform when compared to others. This is where the third step is \ninitiated as it allows the company to provide data-driven services to \ncustomers using data from all customers. Now, customers can benchmark \nthemselves and understand where to improve and where to extend their \nlead over competitors.<\/p>\n\n\n\n

The fourth step is where the company moves to find alternative \nmarkets\/customers for the data from its primary customer base. Here we \nsee the start of a two-sided market where the primary customer base \ngenerates the data that is then monetized with a secondary customer \nbase. If played right, this can allow the company to transition from a \nproduct to a platform company and to ignite a thriving business \necosystem where the company can \u2018tax\u2019 transactions between ecosystem \npartners and thus create highly profitable revenue streams that, in \ntime, may outweigh the revenues from products.<\/p>\n\n\n\n

In our discussions with companies in Software Center, there are three\n main challenges that companies struggle with, ie pricing, disruption \nrisk from suppliers and partnering. The first challenge, pricing, is \nsimply concerned with putting an actual value on data sets or data \nstreams. The preferred model, though difficult to execute on, is \nvalue-based pricing, meaning that you estimate the value that the \nreceiver of the data gets from it and then negotiate a fair share of \nthat value.<\/p>\n\n\n\n

The second challenge is that product companies are constantly asked \nby suppliers for data. Initially, this concerns data from the subsystem \nprovided by the supplier, but over time, it tends to broaden and cover a\n larger and larger scope. The risk becomes that, with enough data, \nsuppliers can become powerful competitors in data-driven services. They \noften serve multiple companies in the same industry and if they manage \nto negotiate data from all of them, they\u2019re much better placed to \ngenerate a competitive advantage. Of course, many companies have little \ninterest in this, but finding the right balance between sharing and \navoiding creating a new competitor is a difficult one. The best practice\n seems to be the insertion of a control point, meaning that you can cut \noff a supplier at any point in time when it becomes clear that they\u2019re \nstarting to compete with you.<\/p>\n\n\n\n

Finally, even for potential partners from other industries that are \ninterested in gaining access to the data collected by the company, it\u2019s \noften very difficult to decide which of these potential partners are \nworthwhile to participate with and which ones should be ignored. There \nare few generic guidelines here, but in general, a potential partner \nthat can help you build a two-sided market and, in due time, become a \nplatform company is much more valuable than alternatives.<\/p>\n\n\n\n

The embedded-systems (or cyber-physical-systems) industry is becoming increasingly aware of the importance of data but is struggling with operationalizing this awareness into a solid business. I\u2019ve outlined the typical pattern that I see companies follow, as well as the key challenges experienced. Engaging in data is very difficult for companies that still think of themselves as metal-bending experts, but it\u2019s critical to get going. Not using your data, or just giving it to someone else to build a business around, is the worst thing you can do. For all the risks and challenges, in a digitalizing world, you need to be world class at software, data and AI and the only way to achieve that is to experiment and learn. Go digital!<\/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":"

There\u2019s an interesting development going on in the embedded-systems industry. Initially, data was only used for internal purposes and quality assurance. Customers would send log files to product companies who would analyze them to figure out why the product wasn\u2019t operating as it should and what to do about it. Over time, the periodic data … 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\/1147"}],"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=1147"}],"version-history":[{"count":1,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1147\/revisions"}],"predecessor-version":[{"id":1149,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1147\/revisions\/1149"}],"wp:attachment":[{"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1147"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1147"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/janbosch.com\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1147"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}