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Success in sports is based on talent and discipline. In almost all professional sports, however, a technology has been introduced in the last 15 years which has been essential to success. In football, baseball, sailing or golf, only the intensive use of analytical capabilities makes talented and hardworking athletes real winners. This analysis now goes far beyond the evaluation of simple metrics – it is about using high-sophisticated on-field analytics.
The historical success of Liverpool FC over the past two seasons has been based on using incredible data science during matches. Many football clubs have data analysis departments, but very few incorporate such knowledge into top-level decision-making and processes to the extent that Liverpool have.
This does not happen by chance. Ian Graham, the director of the club’s research division, has a doctorate in theoretical physics, while the other members of their data science team include an astrophysicist and a doctor in philosophy. Together, they analyze the match at a granular level by combining event data and tracking data, so Liverpool can comprehend how each action impacts the probability of a goal being scored.
What we can learn from this success for excellence in business
In business, operational excellence also depends on analytical capabilities, but it is fundamental to look at the right places and analyze the relevant KPIs. Where should the focus be on? In football, the phrase “the offense wins games, the defense championships” can be applied in business where we can distinguish between two types of processes: The ones that matter directly to your customers and really set you apart from the competition such as customer service (issue-to-solution) and order processing (order-to-cash); and the ones running in the background but which are no less important such as innovation (idea-to-product) and purchasing (procure-to-pay).
Process mining is the technology that provides ‘on-field analytics’ for core processes
It is important to see that many relevant and leading indicators can be analyzed only by monitoring the step-by-step execution of the processes; it is not enough to look only at the final results of the process.
For example, the analysis of the order-to-cash process shows the effectiveness of your company to convert a product or service into money. This process can be subdivided into subprocesses such as order entry to billing and accounts receivable. Below are some exemplary indicators:
- Order-to-confirmation time, order-to-fulfillment time, order-to-bill time, shipment/service-to-billing time
- Percentage of on-time delivery
- Number of order changes
- Percentage of customers on standard terms
- Percentage of customer receipts received electronically
- Average days of past-due accounts
- Percentage of late payments
Another example of a procure-to-pay analysis showing the co-existence of KPIs and structural analysis:
Put process mining in your playbook
Process mining combines the calculation of metrics with the structural monitoring of each process instance. The outcome is a map for the process owner to identify compliance issues, bottlenecks, process variants, outliers and opportunities for improvement.