Operations managers working in manufacturing are no strangers to Key Performance Indicators, or KPIs. KPIs are controlled and specific measurements which can reveal otherwise obscured data in the production process. KPIs are key to the efficient and profitable management of any manufacturing operation. Without them, it’s nearly impossible for businesses to measure their successes and make smart, responsible decisions while setting new goals for the organization.
In recent decades, the use of KPIs have become substantially more common, more creative and more accurate. However, simply putting the KPIs in place is not enough to yield results. They require careful monitoring and thorough communication, along with swift action based on the data that those KPIs yield.
With the advent of new management technologies (gone are the days of the punch card), operations managers can now identify problem areas in the company’s pipeline—and problem employees—at a glance. Real-time KPI tracking systems, which are routed through one central node, allow managers to gather information without needing to consult the heads of various departments, making more time and space for pipeline employees to do their best work without the added stress of reporting.
This uptick in the use of KPIs makes sense. As operations managers apply business concepts developed at the organizational level to their production systems, it is imperative that they’re able to closely measure the successes and failures of those concepts at each step of production. The cost of poor KPI measurement is a literal cost: it’s easy to lose money through inefficient systems, time theft or damaged product.
But expert deployment of KPIs and other data-backed measurement systems must walk a very fine line. With the sort of precision and control that present-day KPI measurement systems afford us, it is tempting for businesses to implement systems which can quickly depart from a reasonable concern for profit and efficiency into systems which are dehumanizing and demoralizing for employees.
Amazon, for example, is an excellent role model for thorough and measurable KPI implementation. Its systems are renowned for their efficiency and the data collected as part of the measurement process not only bolsters informed business decisions, but backs up profit projections made by the company.
However, Amazon is also an excellent example of what can happen when measurements for efficiency in the production pipeline contribute to an environment which is harmful to its employees.
An April 2019 article published on The Verge preceded the bulk of Amazon’s fulfilment centre employee strikes. In the article, Colin Lecher wrote, “In a signed letter last year, an attorney representing Amazon said the company fired “hundreds” of employees at a single facility between August of 2017 and September 2018 for failing to meet productivity quotas.” At face value, terminating employees for inefficiency is absolutely just—but at what point should inefficiency become a terminable offense? As Chavie Lieber wrote for Vox in December 2018, “Associates are pressured to “make rate,” with the rate number increasing and decreasing depending on the season’s demand. The warehouse’s current packing rate is 240 boxes an hour, Ibrahin says, but it’s gone as high as 400. Associates are penalized if they fall behind this rate; they can get a write-up from a manager if they are too slow, which can lead to them being terminated.”
Recent strikes, walk-outs, and protests have made apparent the absurdities borne from Amazon’s data-backed measurement systems—from tracking every single task for every single employee to timing washroom and lunch breaks so as to not succumb to time theft. Khadra Ibrahin, who is quoted in the above Vox article, had to decide whether she would rather pray or use the washroom on her 15-minute breaks during her 12 hour shifts at the fulfilment centre. Other workers have reported skipping bathroom breaks altogether on their shifts, because the walk to washroom takes them off the floor for too long, impacting their productivity.
KPIs then become a double edged sword. While businesses can’t be responsibly run without them, the damage is high and marked when companies lean too hard into efficiency measurements. Higher rates of turnover means an increase in work for HR, terminating employees and onboarding new hires, for example. When working with unions, of course, all production can come to a grinding halt if strike action is favoured. Employees become frustrated and more difficult to work with; morale plummets. As we’ve seen at Amazon fulfilment centres, employees feel disrespected and, at times, depressed.
So what does a responsible use of KPIs look like? As reported by Klipfolio, bringing employees in on the planning and creation of new measurement systems is crucial. This not only motivates employees to feel more invested in the systems which they themselves help create, it makes space for employees to raise concerns about those KPIs, potentially avoiding conflict situations like Amazon’s. Planning new efficiency measurement systems also brings out creative solutions from employees who, undeniably, know the realities of the manufacturing pipeline the best. It gets everyone on the same page and encourages employees to engage in a coordinated effort to maximize efficiency, stability and profit.
As production and operations managers know well, employee and company morale is nearly as important to efficiency as good, measurable systems. It’s not enough to bring in excellent technologies, because people are not robots—they need to be monitored and measured with a compassionate and reasoned approach. Striking this balance ensures high performance, saving money in the pipeline while maintaining a healthy and happy workforce.