3 Ways to Measure the Value of Automation and Process Optimization

While this Bain & Company paper describes several other considerations such as organizational and training/talent initiatives, an appropriate Optimation focus for the purpose of this discussion is more around automation and process optimization. 

Whether the opportunities studied in a client’s scope of interest is production, product development or test and measurement of any kind, there are three key areas that can measure results quickly and predictably from our experience and with our expertise.

• Return on Assets (ROA) is a good measure of the relative value of an investment, particularly in manufacturing technology, such as process or automation.  When looking at the cost of labor and the total cost of ownership of a manufacturing or test system, being able to predict and be accountable to achieving a solid and acceptable return on the efficiency, reliability, and maintainability of a technology investment is essential.  Our teams consistently support such assessments, diagnosing the comprehensive costs, savings, expenses, and sustaining requirements for any deployed asset or upgrade to one.  Linking the right tools, such as PLCs or DCS systems for instance, to shop floor equipment and ERP and other IT systems in the most appropriate manner, will deliver the maximum results.  Often, it’s a competitive edge and a market differentiator.  Done properly, with the right partner, these systems can double or triple the ROA for a client.
• Beyond selecting technologies for connectivity, integration, and automation as above, a critical step is to determine the desired impact on Key Performance Indicators (KPIs) that management use to drive the business and guide e investment decisions.  When properly implemented, automation and optimization efforts tie these KPIs down to operational methods, measureable in ways that people value, understand, and can relate to.  More than merely speeding up operational procedures, Optimation works to thoroughly study, understand, and align these management objectives and technology abilities to deliver the best outcomes.For instance, a recent project we managed for a producer of specialty chemicals needed to concurrently adapt a fixed set of mixing systems in a variety of custom vessels, processing systems, cleaning requirements, and other critical parameters, all with the constant pressure to eliminate or minimize downtime crossover issues, and batch sizes. It wasn’t enough to simply add more equipment, control, or smarts to the system; the interconnectedness of these required a high-level understanding of the existing and potential future combinations, ingredients, and systems that were to be encountered.  As Bain points out, globally these challenges go beyond what conventional approaches of more, more, more can deliver; indeed, we find that often less is more in that simply throwing equipment, people and money at a problem is actually a sure way to ruin your ROA and justification, killing a project before it leaves the drawing board.
• Sensor innovations, and the tools to apply the Big Data resulting from them, is more than a fad.  The frenetic pace of development and innovation in the universe of sensors today and tomorrow open not treasure troves of data, but Pandora’s boxes of unexpected consequences. Data storage and manipulation challenges abound.  When collecting so much data, how do you know you have the right, meaningful data, and do you properly or most effectively convert it to management information?  IT studies in manufacturing systems suggest that the industry is behind curve in this area.  America’s collective ability to gather this data exceeds the general means to profit from it.  That is our opportunity. Using data acquisition and analysis tools such as Real-time hardware and software technologies enable us to gather, synthesize and make sense out of the huge volumes of available instrumented systems.  Material handling, test systems, quality analysis and control systems, and more benefit from a rigorous and experienced view of what matters, and why.  Then turning that into actionable information ties together the ROA, KPI and other measures of success and progress that today’s manufacturers seek in this dynamic, hyper-competitive, and ultra-complex world.