Interestingly, data has become one of the more valuable resources available to manufacturers today. Yet, at first blush, its value doesn’t seem to correlate with the laws of economics – supply and demand. In today’s world of “big data,” most manufacturers have reams of data available to assist with decision support – so how can it be both plentiful and valuable?
Business leaders recognize the value of making better decisions based on actual, current data. This understanding has led to a strategy of collecting as much data as possible. Now the challenge is that too much data is being assembled, creating a hindrance to quickly driving value from that data by converting it into intelligence.
How can all this data now be understood? And, how can the use of advanced analytics become seamlessly blended within a business process, given the burden of now having so much data that must be filtered through?
Time to Simplify
The solution must be to simplify the process. A good first step is to avoid the need for skilled data scientists to be part of the process involved with establishing, maintaining and continuously improving business processes. The evolution of data analytics has reached a new chapter. The first manufacturers who learn the benefits of what I’ll refer to as “invisible analytics” will be the first to reap its benefits. Just like H.G. Wells’ science fiction novel “The Invisible Man,” considerable power can be captured by performing actions in the background.
The concept of data analysis is maturing every day. Everyone is trying desperately to meet the baseline of intelligence now expected across all industries. For example, profitable retailers rely on stock visibility and inventory tracking, both of which are powered by data analytics. In order to keep up with ever-increasing customer expectations, retailers must be able to locate, source, assist and deliver any item in their range or risk losing a sale. Clearly, business intelligence is fundamental to delivering a reliable and positive experience for their customers.
In manufacturing, data analytics has become a fundamental activity across every department on multiple devices – from one end of the supply chain to the other. In some plants it is almost mandatory for IT teams to deliver manufacturing performance dashboards and status reports on demand. It is certainly true that data analysis is becoming habitual amongst most forward thinking organizations.
However, many of the conclusions drawn from data happen in isolation without necessarily being placed within the wider business context or forecasting the long-term impacts. Improvements are dependent on whether businesses can keep up with the evolution of the business or manufacturing intelligence systems and welcome new approaches.
An Important Step Forward
The latest innovation on the data analytics maturity curve is the introduction of invisible advanced analytics. As the name suggests, these new technologies embed increasingly complex and sophisticated analytics into business applications. Instead of highly qualified “data scientists” being relied upon to act as human data filtering systems, they can now incorporate analytics processes into their application stacks. Essentially, this will remove the manual, human element and data analytics will become ‘invisible’ to the end user. Substantially complex statistical methods and data science techniques can then be applied in real-time – almost as a form of artificial intelligence. Businesses can then proactively identify pain points in need of attention to then work more efficiently and cost-effectively.
One-off nuggets of valuable information derived from hours of painstaking data mining is no longer timely enough for businesses. Data analysis will exist as an invisible undercurrent informing all day-to-day business activities. It won’t be reliant on users manually switching between different applications in the “transactional world” or the “analytical world.” Instead of running reports and dashboards, advanced analytics will be provided in context as part of the wider business process flow.
For manufacturers, this means having data collection occurring along all parts of the process. This reserve of information will be tied to every product being built, to then become part of the final record for every item made, including all parts, processes and workers that were part of its creation. This type of solution is commonly referred to as having “Global Traceability.” Such a transparent approach allows manufacturers to learn where efficiencies could be made and where to focus improvements.
There certainly seems to be a business-wide consensus that data-driven decision-making is smart and fundamental in a competitive marketplace. Forward-looking organizations will soon realize that advanced invisible analytics removes data mining headaches and offers invaluable insight. It remains to be seen how quickly invisible analytics will become the norm. The data goldmine exists in every business; it is now up to them to discover it!
If you liked this article, here are a few others you might also find interesting:
- Making Sense of Enterprise Manufacturing Intelligence
- Some Manufacturing Intelligence is Smarter than Others
- Manufacturing Intelligence – The Central Nervous System of Your Plant
