Figure 1. "Business Movers" either improved their earnings or profits by 10% or are respondents that improved performance on 10 of the 14 business metrics.
So what does that have to do with instrumentation? Without instrumentation, measuring operations performance is a gigantic tradeoff. In fact, one of the respondents said, "I can automate data collection, but then I must look at the cost-benefit. Where is the line? The tradeoff is between how much unproductive time employees need to capture the data and the expense of capturing the data automatically. Instrumenting the process may be faster and more efficient—but how much does the infrastructure cost?"
Clearly the cost of infrastructure is always a hurdle for investing in automation. How most companies do this today, particularly in the West, is problematic.
- Timeframe: The first problem is that most companies look at it from a short-term investment perspective, and not in the context of long-term ability to improve business and financial performance. From the short-term view, investing in instrumentation may be a tricky justification exercise. However, from a longer-term view, it's nearly certain to be a winning proposition. In fact, taking the short-term hit to margin during the investment phase can be the beginning of a longer-term, year-on-year improvement capability that the company can't envision before the investment is in place.
- Productivity perspective: Most companies do not have a handle on the lost productivity and other costs that result when employees can't see their performance. This could be either not having visibility to how well they're performing—or not seeing performance outcomes quickly enough to take action to prevent problems or improve performance. Another interviewee said, "What I've learned is that the faster I deal with a quality or productivity issue, the less it costs to correct it. Faster means less costly countermeasures."
The cost-benefit question in the quote above illustrates both of those issues. The common approach to justifying an investment in instrumentation is a view of labor hours spent collecting data vs. the cost of the automated data collection capability. That is simply faulty logic.
One of the other interviewees pointed out that the most valuable metric for his company is the cost of lost production time. And what contributes to lost time? All of the things we typically measure. There's a good bet that the quality, throughput, asset utilization, compliance and anything that relies on timeliness (such as cycle times and schedule attainment that enable good customer service) will benefit from better instrumented processes.
We would broaden that to include any lost time in the company and any non-value-adding time. Value stream mapping may contribute a clearer view by considering the entire set of operations metrics that contribute to the company's success. Automated controls enable process reliability and consistency that Six Sigma and other continuous provement methodologies recognize as the core goal. Furthermore, the information available from instrumentation allows people to make better decisions, and can feed other automated systems, such as software applications, to make them more valuable. The justification should work toward quantifying all of those issues.
In fact, business movers are nearly twice as likely to use fully automated data collection to feed their metrics processes as others, as Figure 2 shows. The concept of partially automated data collection involves things such as employees using barcode scanning guns. It should be noted that more than three in five respondents in the "other" group are heavily reliant on people to gather the data required to gauge performance. We doubt this is either efficient or effective.
