We have all heard about the famous Deming Cycle – PDCA (Plan Do Check Act)। The closed loop process developed as a preemptive action to mitigate manufacturing and quality related risks. Globalization of manufacturing in the recent times has taken the battle for efficiency to another level. As we have heard this before – “The battle is no longer between companies or organizations but between Supply Chains”. The outsourcing of manufacturing to the low cost countries has challenged the ones in the developed world to squeeze additional cost out of their supply chain to remain competitive in the new world.
Can we predict failure? Prediction is an art and not a science. However, with new technology and tools we can come close to predicting failure. The successful companies are the ones that can take corrective actions faster. The financial industry has developed a series of metrics to evaluate company’s performance and constantly monitor the metrics to make decisions to buy or sell. Some quantitative hedge funds base their decisions simply on numbers from their quantitative models but the outstanding ones can correlate the metrics with experience and make better and faster decisions. I always begin by analyzing the human body or an automobile. As we grow older, predictive maintenance becomes an important facet of our lives. We go to the doctor on a regular interval, trying to judge the condition of our health. The main reason for doing so is to reduce the future cost and lead a healthy lifestyle. The doctor goes through a series of tests and measurements and provides warnings based on the results. These tests have been standardized and customized based on the individuals’ age and gender. The best doctors take the data and make recommendation based on their experience.
The key learning from visiting a doctor are similar to a supply chain risk management. There are several key components that have to be in place to enable a medium of managing risk in operations. The five key components are 1) Metrics, 2) Real Time Data Gathering & Monitoring, 3) Experience (History), 4) Corrective actions and 5) Perfection.
The most difficult task is defining a standard set of metrics. Identifying the right metrics at the right level of detail is the first step to help decision making. Just like in the medical community, the metrics vary for manufacturing companies. The segmentation of the companies can be in the form of industry, size, innovations and market perception. Today, there are many software vendors who have developed standardized metrics for financial and operations effectiveness. Companies should however, understand each metric and revisit them in regular intervals to ensure that these are still valid based on the current state of the company.
The challenge 30 years ago was the readily availability of the data to monitor the pulse of the company. With new technology it is possible to constantly monitor the resources (equipment, inventory, order, customer, supplier) and generate consequential results that are constructive in decision making. The interval of monitoring and real time data gathering can be set based on the risk of failure or the impact of failure. The technical challenge on processing massive volumes of data and making sense out of it is a reality in the current internet world and will only improve.
As we have all heard before – learn from history. History and experience is a valuable commodity that we cannot ignore. I still remember the dot-com boom era where all of us thought for a period that we were better in investing that the professionals. We were quickly brought to earth during the bust – where most of us were not prepared to get out of the market in the right time. Manufacturing companies also have similar executives and managers who have precious past experiences. All the data and analysis without a context and perspective can all go to waste.
The dot-com boom and bust made me realize the basic art of investing is to know when to get out. The art of decision making to make gutsy calls to make quick corrective actions is mostly based on the individual just like while driving a car in snow, the driver would slow down to prevent any mishaps. As soon as the car skids, the driver takes quick actions to minimize the loss of control. These action at the level of a company are still valid and in a much larger scale. Corrective actions require real time metrics, data and experience to make judicious decisions.
Perfection is a word that I have borrowed from the Lean community. All the above processes can be built and can give significant benefits. To create a sustainable engine the processes of measuring, monitoring and taking corrective action should be built into the DNA of the company. The pursuit of perfection can only be attained if the processes are standardized and accepted as a norm by the entire workforce.
We must be aware that like Deming’s PDCA cycle it is a closed loop process. Each cycle the learning’s should be incorporated into the new knowledgebase and the cycle should continue. Risk management is about proactively measuring and monitoring the right data and taking corrective actions when required. There is a cost associated with laying such a foundation but the benefits of preventing a failure far outweighs the cost of the implementation.
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