They did not have to wait long for vindication. The first signs of a positive shift came within just two months. Nobody could deny the turnaround was under way. Rhenania’s profits quadrupled the following year, and the merits of DMLM were never questioned again.
it acquired one of its rivals, Akzente, and applied DMLM to similarly impressive effect; a further acquisition, this time of Mail Order Kaiser, was completed the following year. In 2001 Rhenania’s record of achievements in the immediate wake of introducing DMLM was described by Börsenblatt, a leading industry publication, as “astonishing”.
BUILDING ON SUCCESS
To say DMLM saved Rhenania is no exaggeration. It is certainly difficult to dispute the sentiment when it is expressed by the company’s current CEO – none other than Ralf Elsner. “On the one hand, Rhenania’s success can be attributed to the management’s courage, leadership and willingness to try an innovative and non-traditional approach,” he says. “On the other, the evidence shows we succeeded because of the robustness of the mathematical model we used. All in all, it made for a powerful combination.” The numbers speak for themselves. In the summer of 1998, when DMLM was first used, the firm was the fifthlargest of its kind in Germany; by 2001 it was the second-largest. The customer database grew by more than 55% between April 1998 and 2000. Rhenania started to consistently outperform the market, having underperformed it for years. The project paid for itself within weeks. Moreover, the company did not just strengthen economically: it also gained a competitive edge. In December 2000
in the age of big data, mathematical modelling has the power to help smaller companies gain a valuable competitive advantage
Since then DMLM has been extended and modified to leverage Rhenania’s customer base even more effectively. Refinements have included the further differentiation and segmentation of inactive customers, leading to better response and reactivation rates. The model continues to serve as an excellent forecasting tool, presaging the development of active customers, sales and profits. It is also a key component of Supply and Marketing Integration (SMI), a seven-stage, profit-maximising process that Elsner began working on in 2004. SMI was designed to go far beyond DMLM’s focus on customer selection, covering the whole decision and production chain to address a vital
issue in the sphere of direct marketing: finding an optimal merchandise mix based on demand. As with DMLM, it was a matter of challenging accepted industry practice. Pricing, variety, inventories and catalogue content had long been decided principally on management assessments and experience. SMI championed a much more scientific approach for the first time– one capable of establishing the profitmaximising pricing of an entire catalogue, as opposed to the individual items contained therein. Again there was resistance. Purchasing department staff and catalogue editors were notably reluctant to embrace SMI, doubting that the use of O.R. could improve on the merchandise mix suggested by their own know-how. The onset of the global financial crisis was instrumental in persuading the naysayers, and by 2009 – the year after SMI’s adoption – total profits were three times greater than in 2007. Today, with the influence of both DMLM and SMI still absolutely central, Rhenania remains in good health – proof, believes Elsner, of O.R.’s ability to make a lasting difference to a business. “O.R. isn’t a matter of size,” he says. “Especially now, in the age of big data, mathematical modelling has the power to help smaller companies gain a valuable competitive advantage. I think our story demonstrates that very well.”
If you wish to investigate the mathematical models developed by Elsner see Elsner, Ralf, Krafft, Manfred and Huchzermeier, Arnd (2003) Optimizing Rhenania’s Mail-Order Business Through Dynamic Multilevel Modeling (DMLM), Interfaces 33(1), 50 - 66 and Elsner, Ralf (2004) Optimizing Rhenania’s Direct Marketing Business Through Dynamic Multilevel Modeling (DMLM) in a Multicatalog-Brand Environment. Marketing Science 23(2),192–206).
46
IMPACT | AUTUMN 2015