TBR believes that creating common terminology and understanding around data is key to successfully implementing an evolutionary digital transformation strategy, one that enables the organization to transform incrementally, as it capitalizes on new opportunities and deals with new challenges. Essential to this approach to digital transformation is an organizational cultural transformation, one that embraces continual innovation and ongoing collaboration across departments and disciplines and that enlists all parties in the process of harnessing organizational data assets to move the organization forward.
The many uses and users of data
It is commonly accepted that IoT represents the intersection of IT with operations technology (OT). This is true, but only part of the story. Business management is another key player in many projects, and TBR believes it should be a component in all IoT projects. In fact, potential users of data from IoT projects extend beyond these three stakeholders, including many of the departments throughout an organization, such as marketing and sales. To deliver the greatest possible value from any project, including but not confined to IoT, all the potential users of the data should be considered in the design and evolution of each project.
In the early stages of the recent surge in IoT, three to four years ago, the different stakeholders were often brought together for workshops or ideation sessions to invent new solutions made possible by IoT. As IoT has become more common and relevant players are more familiar with common use cases such as status monitoring and asset tracking, there has been less need for this challenging and expensive invention phase of IoT projects. Instead, new projects are often undertaken entirely or almost entirely by OT, sometimes working with IT to ensure compliance with company standards. These projects can confidently deliver a positive ROI while only using data for a single purpose, usually operational efficiency. Potential other uses for the data, or from data that could be generated by the solution, are often not considered in the design. This can be a waste.
The data generated from an IoT project often have value beyond the immediate purpose of the project. For instance, data from a status monitoring solution can be used to identify patterns that could predict service-related incidents. Similarly, comparing status reports across different assembly lines or factories might help identify superior or deficient configurations. Status reports could be correlated with operations speed to help identify either capacity problems or the potential for greater capacity. Capacity limitations or windfalls affect both marketing and sales.
The same kind of potential repurposing of data can be found for most IoT projects. Data has multiple uses. Different people within the organization are able to recognize different potential uses. Uses can be classified into short term and long term. Status data is valuable immediately. Indeed, for the purpose of reacting quickly to status deviations, the data has no long-term value. A solution built for only that purpose would often discard the data to minimize project cost, resulting in a loss of the potential value of the data for long-term analyses. To extract the greatest value and meet broader organizational needs, other people in the organization should be involved in the project design.