There are leading and lagging economic indicators.  Experts have debated the role and importance of various data points for years.  Supply chain indicators can be both insightful and misleading.  For example, do increased retail inventory levels foreshadow anticipated sales growth or reflect unrealized sales expectations?

Cause and effect relationships ensures that if one area of the supply chain suffers or thrives other areas will be unfavorably or favorably impacted (thus the concept of the “chain” seems appropriate).  For example, increased production drives increases for both inbound and outbound transportation services while decreased sales can negatively impact every upstream service.

At the same time, evolving business models such as omni-channel can shift demand for services.  Filling individual orders independently eliminates consolidation opportunities, reducing the need for truckload and LTL services while increasing the requirement for small package delivery services.

This dynamically changing environment forces successful transportation service providers to plan ahead and maintain a competitive position no matter the prevailing economic conditions.  Much easier said than done for sure.

Advanced analytics not only make these issues manageable but when integrated as part of a closed-loop operational planning cycle, can transform weaknesses into competitive advantages.  I know this seems counter intuitive and maybe even somewhat inconceivable but in the era of big data the best math wins!

Success is not based upon having the clearest and most accurate crystal ball.  In the end the crystal ball is based on magic and can’t be trusted.  Success is the product of being effectively positioned to support the full spectrum of market conditions.

Rapid scenario generation in the context of transportation planning optimization provides significant insight to the best asset and service portfolio to support whatever comes our way.
This process can be further enhanced through the use of goal programming techniques.  Iteratively solving each scenario with multiple objectives such as maximum revenue, maximum profit and minimal cost results in a plan focused on the absolutely most impactful decision factors.

Cutting resources such as tractors, trailers and drivers during lean times may help manage costs but can profoundly impact the ability to respond when demand for services quickly recovers.  Identifying and executing reallocation or redistribution strategies provides significant advantages to survive low demand while maintaining the ability to proactively prepare for the rebound.

Big data and advanced analytics create the possibilities for continual success and only those companies willing to harness the potential will bravely lead the way.
To learn more about how Solvoyo works with transportation service providers plan better for uncertainties – click here.

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In many ways striving for consistent and continual success is much like the never say die, never quit attitude of the World Series Champion Kansas City Royals!  When every member of the team “keeps the line moving” you start to expect to win no matter the circumstances…and winning sure is fun!