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Business Intelligence and Smart Supply Chains

October 2, 2012


Successful supply chain processes are collaborative in nature. Mountains of information must be exchanged and understood to keep things moving efficiently and effectively. The more complex a supply chain becomes the more important it is to have a system that can monitor and alert logistics professionals when something is amiss. “In today’s constantly changing environment,” writes Nathan Tableman, Vice President of Technology for UBM Global Trade, “it’s evident that companies need access to key data and metrics to meet customer demands, grow and stand out from their competitors.” [“Is Your Supply Chain Intelligent Enough?Supply & Demand Chain Executive, 4 September 2012] The old adage “knowledge is power” has never been more accurate. In fact, Tableman insists that in today’s business environment businesses need “to obtain competitive intelligence; maintain contractual compliance; connect buyers with suppliers; generate sales leads; and conduct market research, all to help grow their businesses and maintain efficiencies throughout their entire network.”


Steve Banker says that, when you are looking for a business intelligence (BI) system to help you manage transportation, you should look for six characteristics: role-based thinking, holistic data sources, root cause analytics, embedded analytics, landed costs, and the ability to follow the money. [“Defining a Cutting-Edge Transportation BI Module,” Logistics Viewpoints, 28 March 2011] Concerning the first characteristic — role-based thinking — Banker writes:

“Roles include transportation planners, managers tasked with making sure carriers are paid accurately, executives that monitor adherence to transportation goals, and the VP of Logistics that has to put together the annual transportation budget.
But there are also external touch points that involve people outside the transportation department, such as the manager tasked with transportation-related environmental, health, and safety performance, or people involved in the S&OP process (longer lead times means increased safety stock).”

In other words, a good BI system must be all things to all people. Each role player needs a particular set of data delivered in a format that is tailored to his or her needs. At the same time, you want all role players to draw from a single set of data so that they are not working at cross-purposes to one another or basing decisions on different sets of data. That is why Banker’s second characteristic involves holistic data sources — that is, one version of the truth for the entire company. He notes, “BI solutions often need to pull data from a variety of IT solutions and external data sources. And they may need to export analytics to other BI solutions.”


Banker’s next characteristic — root cause analytics — is also important because there is a big difference between being aware of a symptom (such as knowing a shipment has been delayed) and knowing what is causing that symptom. Root cause analytics can be used as an input to Banker’s next desired characteristic — embedded analytics. Systems that can identify the perturbative (i.e., cascading) effects of a delay or disruption are much more useful than a system that simply notifies you that a delay has occurred. “It is often not enough to find a problem,” Banker writes. “Companies also need to enforce behaviors that alleviate it. The more automated this can be the more money companies can save.” Helping companies understand the costs involved are what his final two characteristics — landed costs and the ability to follow the money — are intended to do. Writing about landed costs, Banker states:

“Most companies want to know their true profitability by product and customer. Accurate transportation costs are an important input to that calculation. A BI module that calculates this based on finalized freight audit data, and thus includes unplanned accessorials, will be more accurate than a system that uses projected costs coming out of the tendering engine.”

Tableman’s article looks specifically at the commercial shipping industry. He writes:

“In this industry, access to business critical data is crucial to ensuring the success of large-scale cargo deployments and complex supply chains that span diverse geographical regions and markets. However, delivering timely access to data in this particular industry is difficult as information spans multiple sectors, arrives in different formats and must be standardized before it can be of any value.”

Integrating disparate data is always a challenge; but, it is an essential capability of any good BI system. Tableman notes, “The primary source of this divergent data are Bills of Lading (BOL), the formal documents that contain the routing, parties involved and contents of all maritime shipments that enter and exit different nations.” Although that may sound straight forward, Tableman reports that various countries and regions treat BOL data very differently. He continues:

“Along with the BOL data, there are multiple commodity, statistical and other internationally standardized data sets which combine to generate the massive amounts of data that make actionable business intelligence (BI) necessary to address such factors as knowing which trade lanes are over-booked; or how to ship to the U.S. and avoid possible delays because of labor issues. With these divergent data sets, a variety of national languages and variations in things as simple as the spelling of a port or name of a supplier, combining this information to create intelligence can be very time consuming and costly. Raw data is like any raw material in that the quality varies over time. This also presents a large scale challenge: ‘How do you clean up the data to a level that is perfect without having to read through every one of millions of data points a day?’ To conquer this challenge requires innovative ways to clean, structure and map data points. Without such technology—and at times manual input—data would be unusable.”

Tableman makes two important points I would like to stress. First, a good BI system provides more than just information. As I noted above, a system should be able to identify some of the perturbative effects of a disruption and even offer recommendations about how to mitigate those effects. With a work stoppage looming at some U.S. ports, one can understand why this would be important. Second, supply chains are so complex and the amount of data that must be analyzed so large that technology is essential for meeting the challenge. Enterra Solutions utilizes its Sense, Think/Learn, Act™ platform for many of its supply chain solutions because we understand that near real-time information can only be provided if artificial intelligence is employed. Tableman writes, “As the industry grew into a more complex environment, companies were forced to adapt more robust technology products.” He goes on to explain how his company, UBM Global Trade, uses technology to help companies “process volumes of data effectively.” He continues:

“We allow these technology stacks to take on the load of standardized tasks—like audit, monitoring, statistical model and report generation—and many others so our teams can focus on developing proprietary algorithms to do the more complex components in our processes. Our customers range in how they accept and utilize our intelligence in their enterprises; from raw data dumps to sophisticated graphical representations of movements across trade lanes. But regardless of their technology needs, it’s imperative that we provide them with unfettered access to data analysis in whatever manner they require.”

Tableman concludes, “For all industry stakeholders—including suppliers, buyers, logistics managers, cargo airlines, railroads, maritime shippers—businesses intelligence proves invaluable as they attempt to maximize efficiency and mange flow across supply chains.” One thing that neither Tableman nor Banker discussed, but which I believe is essential for any good BI system, is visualization. Fabrizio Brasca, vice president for global logistics at JDA Software, reminds us that there is a lot of truth in old saying, “A picture is worth a thousand words.” [“Next Generation of Visualization and User Interaction,” Logistics Viewpoints, 6 September 2012] Brasca reports that at a recent conference he attended at MIT “there was one particular view that emerged consistently at the forefront of everyone’s mind. The issue was visualization and usability.” I have repeatedly noted that information that is presented in way that is difficult for users to obtain or understand is little better than having no information at all.


Brasca indicates that as the conference discussion continued participants made it clear that there remains a “need for more intuitive interfaces that mask complexity, define metrics, and aggregate views designed to synthesize the abundance of available data into something actually digestible for both the day-to-day user as well as the supply chain senior executive.” Brasca points out that the need for an understandable interface does not diminish the need for a sophisticated analytic system behind it. At the conclusion of his article, Brasca offered “a few directional thoughts that … are critical when thinking about the next generation of user interaction.” He writes:


  • A picture is worth a thousand words – As a rule, people understand and react to images better than they do streams of data and tables. Metric-enabled graphics, intuitive and directional alerts and representative maps can all be effective tools to communicate information to a user.

  • What I want, when I want it – Configurability is becoming more and more important as an enabling factor to user productivity. The ability to not only decide what I want to see but also the sequence and importance can dramatically increase ease of adoption.

  • More than one way – Mobility has become a fact of life for the average consumer, let alone the supply chain practitioner. Enabling views on multiple formats for different levels of the organization without having to be a slave to a desktop creates organizational synergy.

  • Enable change – I have long been a proponent of the interoperability between planning and execution in the transportation space. Along those lines, interfaces should provide effective ways for users to digest and act on rapid changes that occur within their domain through a combination of sensitivity-based alerts, embedded actionable analytics and powerful underlying engines that can weed through available ‘big data’ and suggest courses of action.”


I agree with Brasca that ideas like those presented by Tableman and Banker must be merged with new and exciting visualization techniques if companies are going to get the most from their business analysis and intelligence systems.

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