Evolving Business Intelligence For Manufacturing

As data analytics and business intelligence continues to find value across many industry areas, the manufacturing industry has been no exception.  In the ever increasing world of looking for efficiencies and dealing with fierce competition, many progressive manufactures have been looking for ways to unlock the value in the data that they have.

dataI’ve had the pleasure over the last couple of years of working with several manufacturing companies that have undertaken various types of BI related initiatives ranging in scope and service.  Through this work, it’s given me the opportunity to assist manufacturing companies in creating dashboards to help visualize the data behind various Key Performance Indicators (KPIs) and ultimately, gain some insight that they can then take action on (at the end of the day, we need to find meaning in the data so we can act on it, otherwise, there is no point in carrying out a BI exercise).  Most of these dashboards have been sales related, looking at revenue generated, quantities shipped, customer profitability, age of entered orders and other such metrics.  Of course these are all hugely important, and of course, there are many many more types of KPIs to be considered.  Perhaps in a future post I’ll write about various types of visualizations that are useful for manufacturers to consider.  But today, one thing struck me – what about operation dashboards?  Dashboards that aren’t necessarily being utilized by senior leadership, but rather, actively being used by frontline workers.

The first thing to consider in this scenario is how would the dashboards be accessed.  While executive level dashboards are being accessed from their computers and mobile devices, this scenario could benefit from leveraging digital TVs / screens that are in common areas.  Careful attention to the design of the dashboards will need to be considered since users would not be able to manipulate the data like a traditional dashboard.  Data would be aggregated and there would be no way to provide drilldown capabilities to granular data.  Dashboards would be designed to clearly communicate key data trends and/or exception-type reporting to alert users to action that might need to be taken.

Some examples that could be considered might be:

  • Scrap Metrics:  provide a visualization so that people on the manufacturing floor can see in real time what the current defect rate for particular products might be.  This is especially useful because scrapped product has a material impact on the cost of manufactured goods and being able to deal with this as it happens rather than reflect on it well after the fact could be of great benefit to a manufacturing organization.  By visualizing the data in a BI dashboard that is being displayed on the manufacturing floor, workers can see the defect rate / trend and take action to correct it.
  • Downtime Metrics: Another huge impact to manufacturing operations is downtime of equipment (and hence another cost to the organization). Whether it is planned downtime, unexpected equipment failure, or some other process related issue that halts equipment utilization, real time visualization of these KPI trends can be invaluable.  Operators who notice early warning signs can act on that information and proactively prevent lengthy down time periods.

The above are simply two examples that could then spark further ideas for leveraging dashboards in a non-traditional way.  With the increasing connectedness of manufacturing equipment, machine generated data will become ever more available to companies.  The key, as in any BI initiative, is to approach that data strategically, carry out some agile, short burst projects that you can learn from and develop dashboards that truly align to how your end-user works.



Categories: Business Intelligence, Dashboards, Manufacturing

Tags: , , , , ,

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