Digitalising machinery companies: Starting with data

Posted by Rohit Chikballapur on September 19, 2019

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  • This month, we have had great conversations about the service digitalization strategy of leading machinery companies in the Nordics. The companies we met generally fell into two categories – those whose digital plans were primarily about developing IoT-enabled service offerings and those that had a more strategic approach to serving their customers, across the entire service-driven customer experience spectrum. The latter demonstrated a much better understanding of the challenges of going from nice looking concept prototypes to building services that customers were willing to use and pay for.

    Don't get mad with data, get even.
    Don’t get mad, get even (with data).

    While every company spoke of a “full-stack” digital service platform as the future of their Industry 4.0 strategy, most complained that their data was nowhere ready to make that leap. Though data is critical to get right, companies lose a lot of time cleansing and structuring data that does not deliver the same business value. Here was our recommendation to them based on our own experience with data in the machinery business.

    Data Transformation 101: Accept that you will be working on data for a very long time

    ·   Most companies treat data cleansing as a project. Of course, it should always begin with a well-structured project and strong executive sponsorship but it shouldn’t end there. If not, as soon as the project is over, data quality will start to degrade.

    ·   Digitally ambitious companies recognize that data management is an ongoing responsibility and put in place people and processes to manage this.

    Data Transformation 102: Prioritize your data cleansing activities based on the potential for immediate value

    ·   Most companies try to “boil the ocean” when it comes to getting on top of their data. As a result, 12 months down the line, none of the projects are finished, the business functions don’t see returns on their efforts and often revert to their business as usual.

    ·   Prioritizing the data handling activities based on the potential for immediate value enables companies to break this massive problem into byte-sized pieces.

    ·   Not all customers and regions are at the same digital maturity levels.

    In my next post, I will expand on these thoughts with “A sequential approach to data maturity” that we recommend to our machinery clients:

    A sequential approach to data maturity - driving business value early from data cleansing activities.

    Roy Chikballapur, CEO & Co-founder @ MachIQ Software