In a previous post, I wondered why, if there is so much data available, businesses continue to miss the mark. The PC industry is one example. In the fourth quarter of 2012, PC sales weren't anywhere near where vendors and analysts expected. One reason is the seismic shift occurring in the PC market as users move to tablets and smartphones. The other reasons can be consolidated under "Our best guess was wrong."
The phenomenon of big-data -- the collection of information from internal and external inputs -- is expected to improve the supply chain. One key function of the supply chain is forecasting demand, and big-data will parse overall demand information into increasingly granular segments -- who is ordering products, where they are ordering from, what color they prefer, and so on. The better the data, the thinking goes, the better decisions businesses will make.
This type of information is already available through supply chain systems. ERP/MRP systems analyze the big picture. POS data is more granular, and SKUs narrow things down to specific items that were ordered. However, this data is being shared only within a specific supply chain network. Big-data will share that information with any partner that could benefit from it. The consulting firm McKinsey said in a 2011 article (registration required) that sharing data will be a major obstacle for businesses to overcome.
One big challenge is the fact that the mountains of data many companies are amassing often lurk in departmental "silos," such as R&D, engineering, manufacturing, or service operations -- impeding timely exploitation. Information hoarding within business units also can be a problem: many financial institutions, for example, suffer from their own failure to share data among diverse lines of business, such as financial markets, money management, and lending. Often, that prevents these companies from forming a coherent view of individual customers or understanding links among financial markets.
Some manufacturers are attempting to pry open these departmental enclaves: they are integrating data from multiple systems, inviting collaboration among formerly walled-off functional units, and even seeking information from external suppliers and customers to cocreate products. In advanced-manufacturing sectors such as automotive, for example, suppliers from around the world make thousands of components. More integrated data platforms now allow companies and their supply chain partners to collaborate during the design phase -- a crucial determinant of final manufacturing costs.
There are, of course, many more challenges. McKinsey makes a point particularly pertinent for the electronics supply chain: When it comes to big-data, not all industries are created equal. The nature of an industry's inventory is one of the differentiators. In real estate, a potential customer's demographic data (children, income, current neighborhood, etc.) is quite valuable. In this case, the inventory (the home) already exists. In the electronics supply chain, things are different -- inventory is built in response to estimated demand.
Christian Verstraete, chief technologist for cloud strategy at HP, wrote in an EBN/Velocity magazine article, "Let's Move Supply Chain Collaboration to the Cloud," that the electronics industry is still limited by time and space. In most cases, it takes two to three months to build components and six weeks or so to ship finished goods around the world.
It may be way too soon to gauge big-data's impact on the electronics supply chain. The McKinsey article said big-data also requires tools such as established and emerging IT infrastructure in the supply chain.
At the outset, we'll acknowledge that these are still early days for big data, which is evolving as a business concept in tandem with the underlying technologies. Nonetheless, we can identify big data's key elements. First, companies can now collect data across business units and, increasingly, even from partners and customers (some of this is truly big, some more granular and complex). Second, a flexible infrastructure can integrate information and scale up effectively to meet the surge. Finally, experiments, algorithms, and analytics can make sense of all this information.
Electronics companies are beginning to use the cloud to manage big-data. Avnet Inc. (NYSE: AVT) is using E2open's cloud-based platform for its Control Tower offerings. Control Towers give users real-time visibility into supply chain activities and help them share that information with pertinent partners. It's one way to break through the silos of big-data -- and possibly reduce the impact of best guesses.