Business Intelligence in the Supply Chain

Business Intelligence in the Supply Chain

Thanks to business intelligence tools, companies are no longer awash in reams of data that they don’t know what to do with. Instead, logistics managers are using BI technologies to find real meaning in their sea of numbers—and take actions that boost supply chain efficiency and effectiveness.


The 6 Best BI Modules For Transportation Management Systems

The definition of business intelligence (BI) depends on who you ask.

"An umbrella term that includes the applications, infrastructure, tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance," says research firm Gartner.

"Business intelligence is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information," according to Wikipedia.

"Business intelligence is the use of computing technologies for the identification, discovery, and analysis of business data such as sales revenue, products, costs, and incomes," notes Techopedia.

Regardless of its definition, many companies today are embracing business intelligence tools. And BI has become a must-have for the transportation and supply chain sector. Business intelligence/analytics is the highest-ranked functionality requested by customers, according to a recent ARC survey of leading transportation management solution (TMS) vendors.

Several factors are driving the demand for BI within the transportation and logistics space. "Companies want more granular visibility to their transportation spend so they can manage and control it more effectively," says transportation analyst Adrian Gonzalez. "They want to identify negative trends in costs and performance—and identify root causes—as early as possible to take corrective action. And they need to conduct ‘what-if’ analyses to evaluate the service and cost trade-offs of different transportation strategies and tactics."

Companies are most attracted to supply chain BI tools for their coveted ability to make sense out of the seemingly endless array of data that has become available through the continuing adoption of logistics technologies such as TMS, warehouse management solutions (WMS), and supply chain execution systems. While access to data is key, being able to find, understand, and use that data to make strategic decisions that improve supply chain effectiveness is crucial.

Turning Data Into Information

"Business intelligence allows companies to turn data into information—that capability is where we draw the line between standard reporting and BI," says Chris Johnson, vice president of research and development for LeanLogistics, a transportation technology and solutions provider based in Holland, Mich.

"Historically, reporting has been about merely extracting data—getting it out of a system and into a spreadsheet or a database, where a company would then try to slice and dice it, and turn it into useful information," he adds.

Today’s BI tools are taking that extra work out of the equation, offering up data in easy to understand and digest informational formats, presented in a more visual way. BI tools for supply chain users typically fall into three categories:

Reporting. Business intelligence reports are far more detailed and dynamic than in the past. "BI reports display all the data about transportation providers as usable information, in a scorecard format," Johnson explains. "Factors such as on-time delivery, tender acceptance rate, and meeting capacity commitments are assigned metrics and weighted averages to help users determine how well carriers are performing overall.

"The point is to use that information as a foundation for productive discussions with supply chain partners," he says.

Real-time dashboards. Managers and executives who want a quick, daily overview of what is happening in their transportation or supply chain network use dashboards, which provide information in near real-time to help users catch—and solve—problems as they occur.

"Dashboards make it easier for users to identify trends and exceptions, and to analyze specific components of their transportation operations more intuitively," notes Gonzalez.

LeanLogistics offers two standard BI dashboards for its TMS users (companies can also create their own): dispatch console and supply chain monitor.

"The dispatch console shows high-level information that gives a glimpse of business activity, such as: How many loads am I pushing through today? How many have been assigned to carriers? How many have appointments?" Johnson says. "The supply chain monitor is an exception-based tool that provides visibility to red flags such as loads that are supposed to be picked up tomorrow but haven’t been assigned yet."

Dashboards also give companies the advantage of quick reaction time. "Because dashboards are updated as business is occurring, users don’t have to wait for someone to compile and send reports. Therefore, they can react faster to changes in the market," says Cindy Winkel, vice president of data warehousing and business intelligence for Frisco, Texas-based 3PL and technology provider Transplace.

If, for example, capacity requirements are not being met on a certain lane, a dashboard makes it easy for users to spot tender rejects occurring within that lane, check into the problem, and possibly rebid the lane.

Benchmarking. Comparing data on factors such as freight rates and on-time delivery percentages against peers allows companies to get a more complete picture of their performance in the marketplace.

Take freight rates, for example. Rates have flexed up and down along with the economy recently, so nabbing a four-percent reduction in rates may seem like a good deal, until you compare it to others in the industry.

"If benchmarking identifies that rates overall are down eight to 16 percent, then that four-percent reduction is no longer a good deal," Johnson explains. "Having access to that information allows a shipper to renegotiate with carriers."

Many companies are also using BI tools to highlight patterns found in historical data that may yield clues to future risks and opportunities in their supply chain or transportation networks. This predictive analysis capability uses real-time data-driven insights to speed decision-making and help create a nimble and responsive supply chain.

BI in Action

So how are shippers using BI to improve supply chain and transportation operations? Ultimately, it’s about translating the information provided by BI tools into actions that achieve goals such as improved supply chain efficiency, reduced costs, better customer service, or improved relationships and strategic partnerships with logistics vendors.

The methods shippers use to put BI information to work range from simple to complex. "Some shippers use BI tools simply to categorize their supply chain costs at a more granular level than they have historically," Johnson explains.

On the more complex side, companies can utilize BI tools to further drill down into the supply chain, and drive out even the smallest inefficiencies.

One shipper, for example, consistently netted a 92-percent on-time delivery rate for its loads, but wanted to get to the root of the problem dragging down the other eight percent of shipments. Was it the geography of the lanes? Not enough lead time? A problem with the carrier or the equipment?

With the help of LeanLogistics’ BI tools, the shipper narrowed down the number of potential delay-causing variables, and determined the culprit was geography: loads in a handful of lanes were late more frequently than loads in any other lanes.

"The company discovered that shipping from Point A to Point B in these lanes would always carry some risk," Johnson explains. "But having that knowledge up front let transportation planners narrow their focus to those likely points of failure."

In this example, the power of business intelligence opened up a variety of options for handling these late loads: the company could build in extra lead time for shipments in these lanes, or source those customers from a different DC to avoid congestion, for instance.

"Going after the last 20 percent of the supply chain that might be functioning sub-optimally is where BI can really make a difference," Johnson says.

Better Decisions Through Data

Optimizing performance across the supply chain was a key factor in Anna’s Linens’ decision to embrace BI tools. The company, based in Costa Mesa, Calif., is the country’s 14th-largest retailer of home textiles and décor items. A family-run business with more than 3,200 employees, Anna’s currently operates roughly 320 stores in more than 20 states.

The company uses a business intelligence portal from Transplace to access a suite of reports and dashboards that provide clear visibility to its transportation performance.

"We have access to more than 50 different metrics and key performance indicators via the Transplace BI portal," says Miles Tedder, senior vice president of IT and supply chain for Anna’s Linens. "They encompass most, if not all, industry standard transportation metrics such as tender, acceptance, delivery performance, volume, cost, trends, service levels, length of haul, cube per load, and weight per shipment.

"The data is presented in a comprehensive set of formats—graphs show trending visibility, and radial dials display performance within ranges—based on type of data, data elements, and how we analyze them," he explains.

Delivering this BI data via real-time dashboards and reports makes it easier for Tedder and his team to use the data to make operational decisions quicker and more efficiently.

"The depth and frequency of data available from Transplace provides us the necessary basis for process decisions and strategy evaluation," Tedder explains.

"Businesses that have utilized TMS for years, and are used to searching through reports for relevant data, experience a cultural and conceptual shift when they adopt BI tools." Owen Smith, senior vice president, product strategy, Cadec

For instance, the BI data called to management’s attention a drop-off in delivery performance that occurred in a certain lane within a short time. Examining this red flag closer, the company decided to change carriers to fix the problem.

"We were then able to monitor performance to make sure it improved, and see if we incurred any costs associated with the change," he says.

Having the BI data has also kept the company from over-reacting when issues arise that do not signal a larger problem in the supply chain. Sometimes, Tedder notes, exceptions are just that—exceptions.

"One store may receive a late delivery due to any number of issues," he says. "With BI capabilities, we can determine if one late delivery is just that, and not a broader issue. It also allows us actionable visibility to performance and cost information, enabling us to optimize our results. Without the BI portal, we’d have to devote time and resources to sifting through a lot of data."

Say Goodbye to Data Mining

Tedder’s observation about saving time is right on target. The switch from sifting through data to find problems or trends to having relevant, exception-based data pushed directly to users is one of the biggest advantages of BI tools. It is a near-revolutionary change in the way companies approach data—and in some cases, the way employees do their jobs.

"Managing by exception is better than mining for data," says Owen Smith, senior vice president, product strategy for Cadec, a fleet management solutions provider based in Manchester, N.H. "Businesses that have utilized TMS for years, and are used to searching through reports for relevant data, experience a cultural and conceptual shift when they adopt BI tools."

That was the case for Valley Proteins—a Winchester, Va., company that recovers, renders, and recycles animal by-products—when it began using Cadec’s BI tools. The company, which operates 22 facilities and a fleet of roughly 450 trucks, began using Cadec’s PowerVue solution in 2012 to give fleet managers real-time, actionable information on fleet and driver performance, as well as pickup and delivery details.

"Our employees were used to data mining. ‘Let’s dig into the data and see what’s going on’ was our culture for years," says Paul Battista, Valley Proteins project manager. "Now, with BI, we receive exception-based transportation information, which gives us more time to manage drivers instead of searching for data."

Freeing up time to manage drivers is particularly important to Valley Proteins because the company operates two distinctly different sides of the business.

"We do street-level routing, where our drivers pick up products at restaurants, grocery stores, and small slaughterhouses; we also deliver full truckloads of products," Battista explains. "These are two completely separate operations that have to be managed separately because the drivers are performing different tasks."

To ensure its fleet is operating at maximum efficiency, Valley Proteins counts on the business intelligence provided by Cadec’s PowerVue tool. Exception-based reports, such as planned-vs.-actual routes, help Valley Proteins managers quickly flag drivers that have taken too long or made too many stops on a certain route.

"Using these reports frees our managers from worrying about drivers who might be a little off on a route, and allows them to quickly find the drivers that went, say, 150 miles in 14 hours when they were supposed to do 100 miles in a 10-hour day," Battista explains.

"We can drill down into these exceptions to find out what is going on—did the dispatcher plan a poor route or did the driver incur extra miles by going off route to eat lunch at a favorite location?" he adds.

Dealing With Red Flags

When red flags such as these pop up, the company now has an easier way to analyze the data, address the issues with drivers and/or dispatchers, and determine which options it should take as corrective action.

"We look at these exceptions case-by-case," Battista says. "Sometimes we have to make a change in our dispatch operation, and sometimes a change in driver behavior is necessary."

Battista also reports a greater level of efficiency within Valley Proteins’ fleet as a result of the PowerVue solution and the BI it delivers. "Being able to optimize routes and driver behavior as a result of the real-time data we get from our fleet management system has been beneficial," he says. "We never had this kind of insight into our fleet."

Insight may be the best word to describe the power of business intelligence. By gaining insight into the inner workings of their supply chains through specific, detailed, and actionable exception-based information, companies are making strategic changes to transportation and logistics operations in real time. The end result: greater supply chain efficiencies, cost savings, and operational improvements. If that’s not intelligent, what is?

The 6 Best BI Modules For Transportation Management Systems

What factors comprise a good business intelligence (BI) module in a transportation management system (TMS)? Here are six capabilities to look for:

1. Role-based Thinking: Roles include transportation planners, managers tasked with making sure carriers are paid accurately, executives who monitor adherence to transportation goals, and the vice president of logistics who has to put together the annual transportation budget.

But external touchpoints also involve people outside the transportation department, such as the manager tasked with transportation-related environmental, health, and safety performance, or people involved in the sales and operations planning process (longer lead times mean increased safety stock).

2. Holistic Data Sources: Not all the data needed for the BI module will come from the TMS. For example, some suppliers are beginning to import the Department of Transportation’s CSA database into a business intelligence engine, then presenting near real-time analytics to shippers who want to work with safe carriers.

Because transportation is an inherently collaborative process, EDI data quality (i.e., whether carriers are sending shippers timely and accurate electronic messages) is another important set of carrier metrics. For traditional TMS solutions, architected to be deployed in-house, this is an external data source. For single-instance, Software-as-a-Service (SaaS) solutions, it can be internal to the TMS vendor’s data set. Some network-based solutions are also starting to provide benchmark data on rates.

3. Root Cause Analytics: Common carrier management metrics include tenders refused by carriers on a particular lane, or the number of billing discrepancies. But are these metrics fair? If a shipper gives a carrier only one day to respond to a tender, then, logically, there should be a higher percentage of loads turned down compared to if a carrier is given five days’ notice. Similarly, a rate curve analysis can help show why tenders are refused.

Another common carrier metric totals the number of billing discrepancies between a carrier and shipper. The implication of this is that carriers with a high number of discrepancies are less honest. However, if shippers can drill down into the accessorial costs, then to unplanned accessorials, then to demurrage by location, they might find that one of their sites consistently makes carriers wait many hours to unload.

4. Embedded Analytics: As the TMS collects information, the data is analyzed and the results fed back into the solution. These results are then used to alter processes automatically in response to changes.

For example, carrier performance may be fed back into the carrier selection process to change the ranking of certain carriers. The information gathered through the execution process helps the system adapt automatically to changes as they occur.

It is often not enough to find a problem; companies also need to enforce behaviors that alleviate it. The more automated this can be, the more money companies can save.

5. Landed Costs: A TMS provides good data on the transportation components of landed cost. 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.

6. Follow the Money: No BI module will have everything. What is most important? Follow the money! A TMS can provide data for better procurement; allow for better mode selection, load consolidation, routing, and load building; and can help minimize carrier overcharges.

These are the main ROI buckets. Metrics that document the savings from these activities allow users to see if they are making progress or going backward, and provide insights on root causes.

Many factors go into making a TMS cutting edge: end-to-end process coverage across all modes, the power of its optimization engine, and a flexible architecture, among others. But more and more, it is business intelligence that differentiates one TMS solution from another.

SOURCE: Transportation Management Systems Worldwide Outlook, ©ARC Advisory Group

Leave a Reply

Your email address will not be published. Required fields are marked *