There is less discussion since Pipple made its appearance at Shimano, producer of bicycle-, fishing- and rowing gear. How did that come about? Numbers tell the truth. Thom van Egmond, CFO Shimano Europe, takes delight in the clarity established by using data.
To further improve customer satisfaction, van Egmond approached Pipple to carry out a process mining analysis at Shimano. Because of the rapid international growth due to several acquisitions, the internal complexity and variety of the organization had been increased, management acknowledged. The company was already employing sales offices throughout a multitude of European countries and was, next to that, working together with different distributors.
The analyses revealed that up to 4000 different ways of processing orders were utilized. “That is exactly what you get when a process is composed of six or seven stages and countries, departments and teams use their own approach at each of these stages.” van Egmond now realizes. Yet another eye-opener were the lead times. “We assumed that all our orders were being processed within a couple of days. However, we actually came across orders that were already open for years.”
Benchmarking and focus
Using the obtained insights, van Egmond was able to benchmark the efficiency of different countries, departments and employees based on hard evidence. An aid to largely reduce the amount of discussion: “Data do not lie.” Yet another advantage: the data offered support to management in concentrating on the most promising areas, instead of overhauling everything at once.
Being creative with data
Other projects with Pipple also yielded important efficiency gains for Shimano. For example, consultants at Pipple constructed a model to predict the demand for spare parts on the basis of the number of components Shimano sells to bicycle manufacturers. As a consequence, Shimano does no longer have to rely on the estimates of the retailers.
We predominantly looked at our own data. Pipple made us brainstorm about the possible connections between stockpile data, other information and data outside Shimano.
Pipple furthermore taught the data team at Shimano to be creative. Van Egmond: “We predominantly looked at our own data. Pipple made us brainstorm about the possible connections between stockpile data, other information and data outside Shimano.” Literally ‘outside’, because in this way they discovered that weather patterns are readily applicable to predict sales volume at even the product category level.