With its focus on data management technologies for industrial operational excellence, it’s been a pleasure to be part of independent research firm Verdantix’s latest research, Smart Innovators: Industrial Data Management Solutions.
According to that report, ‘integrating subject-matter experts within data acquisition, cleaning and contextualisation workflows’ is a 2023 priority for the respondents of a recent survey. In the Verdantix’ Global Corporate Survey 2022: Operational Excellence Budgets, Priorities & Tech Preferences, 80% of the 301 senior executives at industrial firms indicated that this would be very important or important in their upcoming data management priorities.
In the long march towards data analytics, data insights, and artificial intelligence it can be easy to lose track of the original ambitious intent of any data management strategy. Verdantix revisits the basics of this intent well by defining Industrial Data Ops ‘as an approach to orchestrating people, assets, processes and technology to acquire and clean a wide variety of data streams, place these in context and deliver as a self-explaining digestible package to decision-makers to help optimize industrial operations.’
Work back from the business problem you’re trying to solve
That’s a lot to unpack but it hits the main complaint that big data projects often trigger, whether they are in industrial operations or across the enterprise. And that is making data and their insights relevant and explainable to business users. That’s why Subject Matter Experts (SMEs) are so important at all stages of the connected-data-to-insights-and-action pipeline.
Subject Matter Experts work back from the business problem they are trying to solve, identify how the right parties should be working together, often in new ways, and develop leading indicators focused on the right outcome to practically advance and manage a program.
Getting to all the data
The frustrations we hear from SMEs focus both on the lack of available data and that the data collected misses the mark entirely. Firstly, the right data is often operations- or even site-specific, not available in the central data lake or lies externally with a supplier, contractor, IOT vendor, or hardware provider.
Getting this sort of data integration onto the delivery backlog of an end-to-end industrial operations digitization project often means it drops off the list or comes too late for an operations team to leverage and tangibly make a difference with it. This could be why a core recommendation from Verdantix in its Smart Innovators report is for vendors to ‘expand data acquisition towards varied, external sources’.
Secondly, even when the data is available the resulting analytics bear no resemblance to the leading indicators sought by the SME, meaning the SME needs to devote extra time to examining the basic processes and data generated in order to reframe the data integration project.
Connect data and expertise around specific use cases
At YuzeData we bring Subject Matter Expertise to these varied external data sources from the start. We do it through domain-intelligent Operations-specific use cases focused on driving efficiency, risk management, and sustainability, that also leverage pre-built configurable connectors to the most used vendor platforms (e.g. IOT data, Asset Management systems, Asset Maintenance systems).
This takes the headache out of the end-to-end orchestration of a variety of data streams and means SMEs can give more focus to the edge case data integrations that are site-specific, which can also be configured and managed through the YuzeData platform.
It’s an exciting time to drive truly expert-driven models, share these across the organization and start driving true performance improvement to multiply that most scarce of resources; true subject matter expertise.
