On Second Thought
with Tom Nightingale
Big data… not since Y2K has there been so much hype about an IT-related term. It’s a term that is relevant to all of us, yet few of us really understand it or what to do with it. Don’t feel bad if you don’t. Wikipedia defines it as “a collection of data sets so large (ranging from a few dozen terabytes to many petabytes of data in a single data set) and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization...”
Big data came upon all of us quickly. According to IT publisher ZDNet
, there are over 2 billion gigabytes of data generated daily (that’s the number 2 with 18 zero’s after it). In fact, with the explosion of data and low-cost storage more than 90 percent of the world’s data has been created in just the past two years.
Package-level tracking data was one of the earliest forms of big data. Major players such as UPS and FedEx led the way in the 1990s by making an amazing level of detail available to both shippers and consignees. Since then two things have changed. First, there is infinitely more data that can be wrapped around that tracking information today. The second is that the rest of the company now generates at least as much data as transportation and logistics and is quickly learning how to apply that data. And that is the part where transportation and logistics professionals seem to be playing catch-up. In conversations with experts in this space, the universal consensus is that our industry is dramatically behind other, margin-sensitive transactional industries. Furthermore, the few companies that are leveraging big data are shippers and they are catching carriers flat-footed.
Recently, Gartner analyst Laura McLellan stated that chief marketing officers will spend more on IT than chief information officers by 2017. This means marketing and other functions will have substantial IT-budgets and come to the supply chain functions to tap into this data. Given the detail available in the supply chain, the rapidly declining cost of data storage, and improving tools, our data will be used to help predict geographic buying patterns, sourcing risks, determine obsolescence cycles, establish credit risks, understand shopper buying behavior, and negotiate warrantee claims.
Supply chain professionals who have not prepared for the onslaught of data requests from other functions need to be ready. A survey by New Vantage Partners revealed that only 29 percent of the drivers behind big data initiatives are coming from operations. In fact, the largest driver in their study was customer and market data. If functions outside the supply chain are not already asking, supply chain professionals should be leading the way. By understanding the potential uses of the big data upon which we sit, we can continue to earn a seat at the strategy table within our companies. On the carrier side of the equation, pricing and profitability data will become increasingly easier to manage. Carriers would be able to finesse pricing programs based on real-time customer data and maximize their returns on the most desirable customer, while expunging customers that stress their systems or make them unprofitable.
Another Gartner report by Douglas Laney recommends CIOs:
- Evaluate infrastructure and architecture elements to ensure adequacy for the anticipated volume, velocity and variety of data.
- Enact more stringent data governance controls to deal with the severe reputation and business continuity risks that come with many big data sources and uses.
- Expand analytics capabilities beyond basic business intelligence (BI) to leverage the full depth and breadth of big data sources for higher-order business value.
- Prepare to make organizational adjustments and be aggressive about obtaining the skills required for specific data management, preparation and analytic needs.
All of which sounds like equally solid advice for supply chain professionals to consider when trying to prepare for (or react to) big data.
For those of us who are not ready for big data, start pedaling — fast. It will require more storage and tools than many of us have dealt with in the past and a different level of access to data from different functions outside the supply chain. It may require some outside help, too. There is no shortage of experts on big data. All the usual suspects have decided this is a growth field in which they can generate lots of billable hours, but to date most are generalists with few offering vertical solutions specific to supply chains. However, big data represents an inflection point and an ideal way for transportation and logistics professionals to be relevant and create value in their organizations. It represents a great opportunity for supply chain professionals to move from telling their companies “what happened” to a far more desirable state of “how we can make it happen.”
Nightingale has held top commercial roles at some of the industry’s leading companies across transportation, logistics and supply chain management. He can reached by email.