This blog focusses on Open Process Automation Forum (OPAF) progress so far and what 2018 holds for it.
Lean,as a popular business process improvement methodology, has become one of the most common business process improvement (BPI) initiative to drive operational excellence (OpEx). Derived from a manufacturing-cetric initiative, Lean is now leveraged in all forms of business. With it's seemingly flexible and easily applied characteristics, is it unable to transform to the customs of Big Data?
At its core, Lean is about focusing on customer value. It either eliminates all processes that do not contribute to creating customer value, or minimizing those that fail to add to value creation. Lean also focuses on processes and value creation that requires the maintenance of a license to operate such as compliance with regulatory requirements, financial reporting, or environmental, health, and safety (EHS) compliance. In simple terms, Lean is characterized as a focus on customer value while eliminating all waste; clearly a BPI approach if ever there was one. However, Lean today is subtlety under attack by emerging technologies and a generational shift in the workforce. The prevailing wisdom in manufacturing is “if you automate bad processes you just end up doing badly bigger and faster,” but advances in technology might just challenge this conventional wisdom.
Lean Demands Focus on Process
Many of the tools of Lean transformation are used to modify business processes to eliminate waste. From “a place for everything and everything in its place,” to value stream mapping, to poka-yoke error proofing; Lean tools are about ensuring that the steps used to deliver a product or service have been engineered to be as efficient and error proof as possible. Lean’s relentless focus on waste reduction and error elimination has yielded measurable and significant benefits to organizations that have used it as a BPI mechanism. As previously noted, if the objective of a Lean transformation program is to simply cut costs, there is a relatively high probability the program will fail to achieve its objectives. Employees typically interpret the Lean initiative as just a way to cut jobs. However, when the focus is on driving customer value by reducing unnecessary activity, support is easier to garner even if the result may ultimately involve reallocation of labor resources. So, Lean done well is really a program of process improvement.
Technology is Redefining Societal Norms
An oft-repeated observation is that smart phones are making people dumber. This is not really a new trend, rather the evolution of one that can be traced back to the pocket calculator. As calculators become ubiquitous people’s ability to solve simple math problems “in their heads” began to deteriorate. The advent of GPS enabled smart phones with voice activated commands of asking Siri to give us directions to the nearest sushi bar has stripped most millennials of basic navigational skills and directional awareness. It is not uncommon to see people leave a building, phone in hand, walk a block and then turn around as the phone informs them they are headed the wrong way to reach the destination they entered. The ready access to information on demand and the ability to rapidly detect and react to bad navigational choices has led to the deterioration of situational awareness for many. It has done so just as the calculator led to a decrease in mental math skills.
Mobility, Cloud, Big Data and Predictive Analytics Could Threaten Lean
The current technology trends that are driving business transformation are mobility, cloud, and Big Data with its associated predictive analytics. In most business or technology journals, we are inundated with stories of how these technological advances, coupled with the Internet of Things (IoT), are going to create whole new business models. Examples of this include how they are already driving services such as the emergence of Uber and Airbnb. At LNS Research, as we talk to suppliers and users, we see a trend of looking to technology to solve what are viewed as otherwise difficult problems. In reality, these problems are often processes run amok. Rather than “bite the bullet” and try to improve a process which usually involve change, something people resist, businesses are looking to analytics and big data to fix their issues without having to change processes. For example, rather than have operators utilize a 5S approach to clean, standardize, and maintain their workspace they want to rely on analytics to just keep track of the chaos so people don’t have to change. The idea is that they can leverage technology to overcome their process shortcomings. Unfortunately, there is some validity to this approach in that technology can help compensate for the chaos or sloppiness in many processes. The risk is that as organizations come to rely on technology to overcome sloppiness they will become evermore lax creating more sloppiness, and driving the need for more technology to rescue them.
A better approach would be to use analytics and Big Data to better understand the process problems and then redesign the process to eliminate the problem. The appeal of technology, which is that it can help avoid the challenge of making change, is a short-sighted approach. Ultimately it could drive an enterprise to such a state of laxness that current technology can not compensate, leading to business failure. Our advice is fix your processes over time and view technology as a tool to help in the short term, and to diagnose. Don’t treat it as a crutch to avoid change.
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