by David Ginsberg, Chief Data Scientist, SAP

Data_Science_color_logoIn the transportation industry, knowing what markets are growing versus those that are declining can make a big difference to the bottom line. Our data science team recently worked with a major railway in North America. This railway is using Data Science and Big Data to better understand market growth and erosion. This is of great strategic importance, since it impacts future company performance.

The railway has found it relatively easy to compare year over year financial results, but they wanted to identify details at a more granular level to gain deeper insight. For example, how much is growth or erosion attributed to macro-economics compared with performance? For areas showing year over year growth, was performance in line with expected growth? Should the company exit certain markets, or aggressively grow others? Which customers and locations are most profitable?

The railway has no shortage of data. From a volume perspective, there can be multiple years of structured sales and operations data, complemented by thousands of macro-economic indicators, structured and unstructured customer data, competitive information, and even social data. From a complexity point of view, there are hundreds of thousands of combinations (location “x” products “x” customer) that must be validated against thousands of distinct market indicators. Fortunately, the framework of developed by SAP’s Data Science team helped the railway gain answers to the questions asked.

SAP’s Data Science team developed unique forecasting models that reside on the SAP HANA platform, and the results can be viewed via SAP BusinessObjects Dashboards and SAP BusinessObjects Explorer views. Crucially, the models separate company performance from market performance at all levels of the hierarchy. Instead of looking at year-to-year comparisons occasionally, growth and erosion can be quantified and ranked at any point in time at all levels. Forecasts are more accurate, and can be updated regularly with the latest data.

At the C-suite level, the company can assess future financial performance and where and how assets should be deployed. For each business area, management can assess how well they are performing; not just how much the overall market is growing. Account managers can assess where their corporate clients are growing the business, and where it is eroding. Data Science and Big Data go beyond forecasting future performance. Strategic insights are possible too. Is pricing a factor for lost business, and how does customer service impact the business? Where is business growing most, and where are the biggest challenges?

In summary, SAP is able to fulfill the promise of Big Data by combining a flexible platform, a range of important software applications, and data science as the secret sauce. For more information, visit

Follow David Ginsberg, SAP’s Chief Data Scientist, on Twitter at @DavidWGinsberg


This blog originally published on the SAP HANA blog and has been republished with permission.