Advanced forecasting in supply chain management – How to exploit the potential of your supply chain data

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Traditional supply chains need to be more agile and flexible, connecting with a broad range of up- and downstream supply chain partners to be able to deliver in the right place at the right time.

The future supply chain

Supply chains of large consumer products companies and retailers are becoming an increasingly important contributor to their overall success. Consumers are demanding instant gratification, a personal approach, and flexibility in how, when, and where to purchase, receive, and consume products. This requires traditional supply chains to become more agile and flexible, connecting with a broad range of up- and downstream supply chain partners to be able to deliver in the right place at the right time. As such, the amount of data exchanges between supply chain partners will increase. But how to stay in control in such a rapidly changing environment?

New technologies enable improvement of your forecast accuracy

Forecasting the baseline demand, excluding any promotional effects, is not the biggest challenge for many companies, though it can still be labor intensive due to the size of the assortment. Improving the predictability of the baseline means employees can shift their focus to managing the disruptions in the supply chain, thereby adding more value to overall business outcomes and decreasing the impact of such disruptions. Next to baseline forecasting, technology can also help to make better predictions of promotional demand, new product launches and the cannibalization effects linked to these dynamics. Besides better supply chain performance, this has direct impact on profitability as well.

Supply Chain Management

New technologies such as machine learning algorithms, but also self-built algorithms in combination with increased computing power, have opened possibilities to combine and analyze large, complex and multiple data sets, thereby improving your baseline sales forecast. Anyone can guess that high temperatures have an impact on the number of ice creams sold, but what if these insights can be further enhanced, for example, by understanding the number of customers that will enter your store or identifying whether there are proven cannibalization effects when other product categories are on sale? Algorithms to monitor these effects are proving to be increasingly effective, and machine learning techniques enable continuous improvement and fine tuning over time.

The impact on your organization

In order to achieve true forecasting excellence, technology alone is not enough. Changes in the organization, processes, and the way people work are crucial to be successful. Cross-departmental alignment, moving to data-driven decision making, and integrated end-to-end processes are some examples of changes that need to be managed. The need for each organization is different and time needs to be spent in detailing these, while in parallel, the technology can be implemented in a series of sprints.

How to get started?

Experience the benefits for yourself and consider implementing a proof of value, a process that takes around two months, depending on the size of data set and the product (sub) category. With a team of experts in supply chain and in data-driven technologies, Capgemini Invent is your trusted advisor and end-to-end partner to implement a proof-of-value and guide you to full scale implementation. We are happy to start exploring the potentials of your organization with you.

For more information, please connect with me.

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