{"id":30233,"date":"2021-09-30T00:00:00","date_gmt":"2021-09-30T00:00:00","guid":{"rendered":"http:\/\/test.tranistics.com\/nvision\/2021\/09\/30\/tms-machine-learning-generates-accurate-comps-after-recent-disruption\/"},"modified":"2026-01-29T07:43:33","modified_gmt":"2026-01-29T07:43:33","slug":"tms-machine-learning-generates-accurate-comps-after-recent-disruption","status":"publish","type":"post","link":"http:\/\/test.tranistics.com\/nvision\/2021\/09\/30\/tms-machine-learning-generates-accurate-comps-after-recent-disruption\/","title":{"rendered":"TMS Machine Learning Generates Accurate Comparables"},"content":{"rendered":"

The chaos of 2020 wreaked unprecedented havoc on the freight transport industry. A true Black Swan event, the COVID-19 pandemic derailed every phase of the supply chain and created backlogs some shippers are still working through today. As the ripples continue to affect global trade, a new problem is emerging: the challenge of pulling accurate comparisons for future data forecasting. The numbers from 2020, 2021, and 2022 are heavily skewed, which makes it difficult to look forward with any real clarity.<\/p>\n

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This presents a real problem for shippers. Without good comps, it\u2019s difficult to facilitate freight operations. How do you budget accordingly? Or benchmark rate averages? How do you negotiate rate contracts in good faith? It\u2019s difficult, but not impossible.<\/p>\n

2020-22 Skewed Comparisons and Much More<\/h2>\n

Freight comparisons have been all over the place over the past few years. If you pull numbers from early 2020, there\u2019s likely some consistency from past years, but pull numbers from over the past 24\u201330 months, and you\u2019ll find major lows. The third quarter saw rates spike, and they\u2019ve only continued to rise since. Clearly, there\u2019s no good way to pull prior-year comps.<\/p>\n

To make matters worse, shippers can\u2019t even rely on sales data from 2020 through 2022 to forecast freight demand. Guidance regarding sales projections is even worse, which only adds to the confusion as shippers and carriers scramble to plan for the end of 2022 and the start of 2023.<\/p>\n

Realigning Comparisons Amidst Disruption<\/h2>\n

So, how can shippers and carriers come to terms with rates? Without the ability to extrapolate from prior-year data in conjunction with forecasts, shippers are turning to more creative modeling methods. The best methods for realigning comparisons to approach accurate benchmarking include:<\/p>\n