A FAN’S Notes: Baseball, Big Data, Wholesale…
A Baseball Fan Looks at Big Data in Wholesale
As a big fan of American baseball, I can get the latest scores, standings, game recaps and lots and lots of individual player statistics with just a few clicks on the internet. My go-to source is MLB.com, the official site of Major League Baseball, (and SAP Business Objects customer), but I also review team web sites, several blogs and the online versions of at least three more traditional publications. What I find is that although this information is available to me, I need to go back regularly, sometimes every day, to update my knowledge of my team, the league and individual performances. Not only do I need to consistently refresh my knowledge base, but I also need to look up some new data points for each team and series as the season progresses.
If it takes this much effort for me, I can only imagine the work that a wholesale distribution company needs to go through to keep track of thousands of customers, tens of thousands products, and hundreds of thousands, if not millions of orders, deliveries and invoices.
When it comes time for a Wholesaler to sort through this data and determine the profitability of each customer, which products carry the highest margin, and how all products should be allocated between multiple branches, the problem becomes much more complex and requires much more sophisticated tools than an internet connection and a search tool.
This is the problem that has been labeled as “Big Data”. To my mind the term does not go far enough, nor does it really state the problem. “Big Data” is out there, and there are lots of sources in addition to internal records to draw from; Things like economic data, commodity prices, weather forecasts, actions of competitors, the rapidly changing trends of consumer opinion as represented by social media, and for some wholesalers, the actions of local, state and federal legislators and regulators.
The real challenge that a Wholesaler faces is how to get at “Big Data” to extract it, put it in usable format and make it available to sales people, supply chain managers, and executives. It is important to note that much of this data is already available, but not in a usable form. Having all this data on a server somewhere, or as more often happens, on several servers, or even individual desktop or laptop computers is of little value
Each of these functional managers needs their own specific data. The sales person needs to know the sales history for each of his customers, their credit history, and what products are on promotion during this sales period.
The supply chain manager needs to know when each customer will accept deliveries, if they will accept partial shipments and backorders, and other site specific information.
Executives need to know sales, sales trends, costs and profitability as well as order cycle times, product availability and other customer service metrics.
If the ability to route data to each functional manager in a format that they can easily consume sounds like an aspiration at best and science fiction at worst, that is just not true. The tools to build this type of world are available today.
SAP Suite on HANA (SoH) offers the ability to put transaction data and analysis tools on the same server by putting all transaction data in main memory. This means that transaction data does not need to be moved to a storage device before being made available for analytical tools such as a data warehouse allowing analysis to be conducted far more quickly and with “fresher” data than ever before. Combine SoH with SAP’s analytic tools, a data warehouse, or SAP’s wide array of mobility apps and the “Big Data” solution is well on its way to being solved. This approach will lead to decisions that are made faster, with current data. It also means that everyone who needs to make a decision or take action is using the same data.
While these tools are available for companies large and small, they would be impractical for the average baseball fan like me. Besides, I have grown to like the searching and scouring for obscure data points that may show some aspect of baseball that I have not seen before. Unfortunately, this year has been a disaster for my team, the Chicago White Sox. No matter how much I search for good news, the fact that the Sox are having an historically bad year cannot be avoided. But just wait until next year