B2B World is Ready for Big Data?

Current big data solution can’t simulate all the factors at same time.

Data model is extremely difference between B2B and B2C. Digital image used by B2C world several years, but I did not see any article talk about B2B customer digital image yet. Because B2B customers are not a person, they are team. Even a small B2B company, it’s still not simply price driven like B2C. Service quality, credit terms, long-term partnership … too many factors build up the B2B data model more complex than B2C data model.

Almost one century before, B2B business boosted by scale production. However, it is against with “have it in your way” model. The DNA is very different. Scale production request standard process, standard procedure, standard model, standard material and spare parts to improve productivity. New internet+ model request the on demanding changes. Every month will have new product/ new service, upgraded service by weekly, by day even hours. It brings a big challenge to traditional B2B company that how to change the existing organization/ mindset even core competence and cultures to compliance with new model. Move back to IT view, it means a lot system need be changed. It is like waterfall development vs. agile development. It is not an easy way for changing. The entire mindset should change first.

Then what the B2B business firms IT should to prepare now? Improve Data Quality is first important thing I think. With China growth in past 20 years, the basic system already be buildup and huge original data stored in database server. The challenge is no one knows whether the data is qualified. I still remember how IT fights with Y2K in 1999. The data qualification is not the focus in last century in china, data have or not have is the key measurement. Even now, some China company still have a lot testing data stored in production database server because no testing environment setup due to cost saving. For big data topic, the fundamental thing is data, if the data quality cannot be controlled and kept stable, we can image how the worst outcome may have.

The second thing I would suggest to do is clean up historical system business logical. In our data warehouse, most of data is come from legacy system in past 20 years. We need clean up those data because some of them are not collected from real data but calculated from legacy system based on legacy business logical 10 or 20 years ago. Those data should be distinguished with real row material data and need be filter by existing business logical to make sure the data quality is stable.

Before we have a consistency row material data pool with senior management team big data mindset build up, I don’t’ think B2B world is ready for big data.