Process Mining for Consumer Goods

The efficient design of international supply chains poses major challenges for consumer goods manufacturers. Process Mining enables an end-to-end view of the supply chain and identifies delays and bottlenecks. The method optimizes ordering processes and contributes to the efficient design of supplier relationships. At the same time, the analysis of throughput times and waiting times reduces buffers and increases delivery reliability.

High material costs and growing sustainability requirements make an increase in packaging optimization a critical success factor. Process Mining takes a holistic view of packaging processes and uncovers waste and inefficient processes. The method enables the optimization of packaging sizes and materials based on actual process data.

Inaccurate sales forecasts lead to over- or understocking and have a negative impact on profitability. Process Mining links sales data with production and logistics processes so that precise predictions can be made regarding demand. It analyzes sales patterns and identifies factors that have an impact on demand. Data is integrated in real time, which refines forecasts and adapts them to market changes. Process Mining for consumer goods thus paves the way for demand-oriented production and optimal inventory management.

The launch of a new product often drags on in the market, which is problematic given the high competitive pressure and short-lived customer preferences. Process Mining analyzes the entire product development process and identifies delays and unnecessary coordination loops that delay the launch. Optimizations include, for example, the acceleration of release processes, the shortening of development cycles and bottlenecks in communication between departments. The analysis of successful product launches establishes and standardizes best practices, which reduces time-to-market and increases the ability to innovate.

Systematic customer feedback analysis is critical for manufacturers of consumer goods. Process Mining links customer feedback with internal processes and enables faster responses to quality problems. The technology analyzes complaint patterns and identifies their causes in the value chain.

In a market with low margins and high competition, pricing is of central importance. Process Mining enables pricing strategy optimization by tracking price changes and their impact on sales and margin in real time. The technology enables the identification of optimal price points by analyzing sales data and competitive information. By integrating cost information, price floors can be determined precisely - for more profitable pricing strategies and higher margins.

The integration of different sales channels poses major challenges for consumer goods manufacturers. Process Mining creates transparency about channel performance and customer behavior in omnichannel sales. For example, conversion rates are identified and order process abandonment is analyzed. The analysis of customer interactions enables the optimal coordination of sales channels. This sales channel integration enables a seamless customer experience across all channels.