Processes and Quality of Cash Flow Forecasting: A Case Study of a Multinational Corporation
|Speaker:||Martin Glaum, WHU – Otto Beisheim School of Management|
|Date:||Wednesday 22 March 2017|
|Time:||14:30 - 16:00|
|Location:||Kolade Teaching Room, Building One|
We provide a clinical analysis of cash flow forecasting at Bayer AG, a large German-based multinational corporation with operations in the fields of health care and agriculture. Our work is based on 20 in-depth interviews with managers responsible for direct-method cash flow forecasting in subsidiaries across 15 countries. We investigate which information they use as forecasting input, how they generate forecasts, and whether forecasting processes are affected by characteristics of local entities (size, complexity of business, etc.). Moreover, triangulating our interview findings with quantitative analyses of forecasted and realized cash flows we analyze whether forecasting practices and entity characteristics impact forecasting quality. Our findings reveal that cash flow forecasting practices vary substantially across the company’s local entities, documenting the limits to standardization and central control in large multinational corporations that operate in heterogeneous and dynamic environments. Furthermore, processes are affected by entity characteristics. Our quantitative analysis shows that cash outflows are more difficult to forecast than cash inflows. For cash outflows, detailed input validation is positively related to forecast quality. The quality of cash inflow forecasts tends to be higher if forecasters eliminate political influences, that may result from internal target setting or other managerial incentives, from operational planning data used as forecasting input.