It is no secret that the US “trade war” with the potential for ever-increasing tariffs, has a direct impact on the current state and future of supply chain operations. With the impending holiday season approaching fast, it is important to note how these two macroeconomic trends will intersect.
Deloitte has published its 2019 holiday sales forecast which, somewhat surprisingly, shows an increase of up to 4.5% compared to last year’s 3.1%. Economic Forecaster Daniel Bachman noted that last year’s numbers did not exactly meet expectations as we experienced a federal government shutdown, as well as declines in the stock market, which more than likely played party to the shortfall.
This year though, Bachman is crediting the expected growth to a combination of new job creation and near record-low unemployment rates. “The economy is still growing, albeit at a slower rate. Additionally, we continue to see consumer confidence elevated, which also helps boost holiday spending.”
The correlation between a busy holiday season and supply chain operations was highlighted through the Council of Supply Chain Management Professionals in mid-September when the cross-sections between multi-platform operations identified many retail factors actively influencing the full circle of logistics; from planning, to inventory, to transportation, to supply chain optimization. The impact a busy spending season has on your operations is not to be ignored.
The rising cost for limited warehouse space is a continuing challenge in the supply chain. A new report (seen above) lists ten U.S. cities that may be most ready to capitalize on the situation. In the table, Phoenix scores the best vacancy rate- still only at 8%. South Florida and Stockton, CA both enjoy an enviable situation with over 6M square feet currently under construction.
Back in a November post, we explored the growth of vertical development in certain real estate markets. Decision makers seek flexible technology solutions such as voice workflows to gain efficiencies in place of expansion or or move. This high demand for industrial real estate is expected to continue – supported by online shopping and the strong economic conditions- and as such, other new options are “popping up.”
Efforts to Match Demand to Capacity:
Companies looking to lower costs while quickly fulfilling their online orders are turning to seasonal or single event pop-up warehouses. Some options are semi-permanent warehousing and can serve to more quickly satisfy certain growing markets or key urban locations. And the pressing demand for workable last-mile logistics solutions is also a driver. There are clear similarities between the on-demand warehouse space and the well known providers in the gig economy such as Uber and Airbnb. All providers aim to efficiently match demand to capacity.
Industrial real estate firms strive to match owners of excess warehouse space with users or retail shippers that need it on a short term basis. The strong growth in ecommerce further challenges the historic warehousing model. This is caused by the need for 3 or even 4 times the warehouse space to assure quick access and handle the reality of increased SKU counts. Blending of technologies is being employed in these new and evolving warehousing space solutions. But the picking of products is still done mainly by human pickers. And in these situations, voice picking can boost both productivity and accuracy by 20% or more.
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Located in Hebron, KY, BlueStar Inc. is a distributor of point of sale and barcoding hardware/software. When their old picking system presented efficiency challenges, BlueStar upgraded to voice for their pick to tote operation. Watch as the management team discusses the implementation, working with the Mountain Leverage team, and overall results.
eBay Enterprise turns to Mountain Leverage to Increase Fulfillment Efficiency and Accuracy:
Faced with enormous seasonal spikes in order volume, eBay Enterprise turned to Mountain Leverage voice to solve their peak season challenges. After moving to voice for picking and packing, eBay experienced a 25% reduction in errors and a 50% reduction in training time.
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