Big Data for Total Quality Management

The age-old notion that higher service and lower costs are mutually exclusive is wrong.

Quality management processes – in conjunction with big data, expertise and collaborative, committed people can enable the confluence of better service with lower costs.

I thought I would use one of our internal data-based processes to share how quality management can challenge the perceived trade-off between cost and service.

In this example, I will just look at a recent transportation management issue that included some intermodal transportation.

What is intermodal? A good definition comes from the Association of American Railroads:

“Rail intermodal is the long-haul movement of shipping containers and truck trailers by rail, combined with a (usually much shorter) truck movement at one or both ends. Intermodal allows railroads, ocean carriers, trucking companies, and intermodal customers to take advantage of the best attributes of various transportation modes to yield an efficient and cost-effective overall freight movement.”

As a technology-enabled logistics company, our people, process and technology platform is constantly optimizing, and part of the optimization includes using intermodal where the cost-service mix makes sense.

For a while now, intermodal – the combination of rail and truck service primarily for carrying long-haul freight – has been growing quickly. The service had improved greatly, and there has simultaneously been an ever-increasing capacity crunch in the truckload sector. Those economics sound like a recipe for growth, and our models have long indicated the wisdom of increasing the intermodal part of the transportation mix. Full steam ahead (no pun intended) growth has all made a lot of sense – that is – until recently.

Lately, a spike in bulk commodity shipments – both in moving agricultural products and to accommodate the growing need to support changes in the burgeoning energy industry have caused bottlenecks throughout America’s rail networks. And that’s already creating trouble for everyone involved – railroads, truckers, and shippers alike. It has become challenging for the intermodal providers to continue at high service levels across an increasingly congested rail system.

With so little marginal capacity in the market, a normally manageable issue became ‘the straw that broke the camel’s back’ – that was the “Polar Vortex.” This past brutal winter weather experienced across the US, introduced a host of complexities to the transportation mix.

Usually, rail is a great alternative when the weather gets rough. The railways are typically a reliable form of transport in bad weather when trucks would otherwise be stranded. This time though, the intensity and length of winter storms had a big impact on both the rail and highways.

In our business, like many others – on-time delivery is imperative.

But, it isn’t all about making sure that ‘the squeaky wheel gets the grease.’ It’s about a quality process that includes a full team with technology that supports the mission.

I will simplify the process a lot, but it still provides a good example of how the quality is built into the business. For one of our programs that uses rail, we have lately had to manage a lot of changes because of capacity and performance.

As capacity issues in the intermodal market manifested themselves, the corresponding service levels tracked by our platform showed declining performance. As a result, particular lanes were changed from intermodal to over-the-road trucking. As we review the past few months we have seen the usage of intermodal dropping from 56% to 35% in one particular program (as an example).

Using data - people, process and technology can conspire to gravitate toward higher quality.

It has been a universal issue. A recent Stifel conference call regarding intermodal had this to say,

“The railroads must find a way to regain network fluidity. Congestion in the Chicago terminal, where many intermodal boxes are interlined from one railroad to another, must be debottlenecked or relied on less heavily as an interchange point. Sufficient numbers of drayage trucks must be available to deliver intermodal boxes from the shipper to the originating rail head and/or to deliver boxes from the terminating rail head to the receivers. Sufficient terminal capacity must be constructed and sufficient numbers of locomotives, rail cars, and boxes must exist to grow intermodal volumes. Absent these conditions, intermodal may lose market share to trucks, which are generally able to provide more time definite service.”

We continue to monitor service performance by challenging our internal processes, our mode selection and managing our carrier base and their performance through the regular work of our cross functional team of management associates that meet and develop ways to improve our process and operation. And, the granularity obviously goes much deeper – for example, some lanes stayed intermodal, but they were switched to different providers.

Once the issues are identified - there's always more than can be done.

In addition to what we can do from strictly a carrier management standpoint, we have improved our order processing functions, which helped overall with improving on-time performance metrics. Areas of focus in this arena included: Improving the timing of client order acceptance and order generation, changes to delivery appointment scheduling processes, and revisions to the assignment of ship dates.

It comes down to tech-enabled continual improvement in discipline in terms of precise and regimented order processing.

These collective efforts have generated clear delivery performance improvements. For this particular program, we have seen a 354 basis points improvement in on-time service. That’s great for customers, but most importantly – consumers will get what they want when they are shopping.

That’s the reason for quality management - our customers' customers.

It’s a detailed look at just one process that maintains one program's price, service and quality, but it provides an inside view of where quality comes from.

Quality comes from thousands of data-based processes that happen each day that protect a key differentiator.

Big data isn't an abstract concept. Are there tangible examples of how your team is using data to improve - more than ever? What skills are critical to using the data correctly? Are you responding to fire drills, or are you making data-driven and process-oriented changes to achieve sustainable quality?

You might also be in, "It’s Not Just About Price and Service."

Dan is the President and CEO of CaseStack, a Board Member of The Center for Retailing Excellence, and the author of Collaborate: The Art of We.

Photo: infocux Technologies and Cuba Gallery, Flickr.