Oil Drills & Apples: Sensors Provide Insight


It has been said that data in the twenty-first century is like oil in the eighteenth century. I don’t agree with this 100%. Like oil, data has to be refined before it is used, and it’s only as valuable as the insights that are drawn from it. Further, oil is a limited commodity —and we all know that the deluge of data is getting bigger every day. And with the proliferation of sensors everywhere, especially in mobile devices, it is much easier to gather data from business operations and also get much better insights from it.

One time, during a mobile device deployment in a distribution center, one operator was describing the distances involved when the system helped execute certain tasks. These were complex and varied maneuvers. Even with all the flexibility, configurability, and flag features in today’s warehouse management systems, configuring something like that completely accurately can be difficult. The supervisor and I walked with this operator to pick an order—and what he said was true: the system directed him to aisle 70, then 71, then back to 35, then to 73, and so on. We were stymied, since this was not how the system was supposed to work. (Of course, in the end, it turned out the problem was a misconfiguration.) What was missing early on was a report that included the number of steps r distance travelled by the operator each day. That would have made spotting the problem quicker—and the road to eliminating inefficiency much smoother.

In terms of distribution center operations, picking is a sensitive operation. It is bound by time, and it contributes directly to the bottom line. Picking faster means shipping orders faster. The faster orders can be picked and shipped, the more orders that can be invoiced, and that brings money in more quickly. Optimizing picking then is critically important—and by reducing steps, you reduce picking time.

Typically, pickers are measured by picks per hours—and so their perceived value is related to their speed as well. That’s not really fair, though, because a variety of elements, including walking distance, order profile, and what orders arrive each day, can impact efficiency. Distribution center managers classify products as Velocity A SKU’s (fast moving or fast selling SKU’s), Velocity B SKU’s (moderately selling SKU’s), and Velocity C SKU’s (slow moving SKU’s).

Fast moving SKU’s go into fast moving locations, while moderately moving SKU’s get slotted into moderately moving locations and slow moving SKU’s into slow velocity locations. This ensures that picking tasks are sorted by location and densely located to maximize picking and minimize walking. Unfortunately, if slotting is not done, or there’s a shift in SKU velocity with a seasonal change, the system becomes much less accurate. Insights around the amount of walking operators need to do would be incredibly useful to the supervisor.

The latest Apple devices we deploy have inbuilt sensors that track many things:

  • Steps.
  • Walking distance.
  • Height.
  • Weight.
  • Heart rate.
  • Respiratory rate.
  • Body temperature.

In a distribution center, steps and walking distance would be most useful. It would make sense to take this data at the department level and draw a bell curve to see the outliers. This could be a powerful tool, especially after a go live where the warehouse management system (WMS) needs tweaking to support the expected throughput.

The same data could also prove useful during performance analysis reviews to analyze operations in an end-to-end process flow of the distribution center. This analysis typically is done before doing a WMS process design to deploy a new WMS.  Any process that has an unusual walking time needs to be analyzed thoroughly and alternates need to be explored to optimize it.

Do you see other ways mobile phone sensors could help with supply chain operation? Let us know your thoughts in the comments section below.

Originally published at Smartgladiator.com on Aug 8, 2016.

Puga Sankara is the co-founder of Smart Gladiator LLC. Smart Gladiator designs, builds, and delivers market-leading mobile technology for retailers, distributors, and 3PL service providers. SG LoadProof is a patent pending Centralized Enterprise Photo/Video Document System on Cloud for Supply Chain. SG LP is built on the fact that photos & videos are vital docs as important as POs/SOs/Legal Contracts/Fulfillment Orders that reside in ERP/WMS/TMS systems, that serve as compelling, conclusive, unequivocal proof of crucial, critical, vital operations executed in Supply Chain within/across orgs when fulfilling customer orders as well as meeting contractual obligations between orgs as merchandise is transferred between different parties that partake in Supply Chain functions & operations. And these photos/videos data should not be stored in someone’s Smartphone or Email Inbox or in their personal/work Computer, but should be stored in a Centralized Enterprise system, where such data can be pushed into super-fast, stored securely, accessible to all stake holders (CFO/Sales Reps/Customer Support/AR/AP) in an org, as well as facilitates super-fast retrieval/sharing. LP is an Enterprise System of record for Photo/Video docs & is as important as an ERP which is an enterprise system of record for POs, SOs, Legal Contracts between parties etc. that have huge legal ramifications, also as important as a WMS (Warehouse Management System) that hold indispensable shipment & fulfillment data on orders. Like how Instagram, Facebook, Snapchat etc. have evolved into social media platforms/systems that enable individuals to showcase their beauty/pretty clothes/lovely cosmetics/hep coolness etc., LoadProof is an Enterprise system that holds similar photos/videos, but for a different reason, not for show off, but to serve as compelling, conclusive, unequivocal & indisputable system of record and proof that can be presented even in the court of law, when there is a dispute between parties while they execute many facets of the Supply Chain functions & operations. Puga is a supply chain technology professional with more than 25 years of experience in deploying capabilities in the logistics and supply chain domain. His prior roles involved managing complicated mission-critical programs driving revenue numbers, rolling out a multitude of capabilities involving more than a dozen systems, and managing a team of 30 to 50 personnel across multiple disciplines and departments in large corporations such as Hewlett Packard. He has deployed WMS for more than 30 distribution centers in his role as a senior manager with Manhattan Associates. He has also performed process analysis walk-throughs for more than 50 distribution centers for WMS process design and performance analysis review, optimizing processes for better productivity and visibility through the supply chain. Size of these DCs varied from 150,000 to 1.2 million SQFT. Puga Sankara has an MBA from Georgia Tech. He can be reached at [email protected] or visit the company at www.smartgladiator.com. Also follow him at www.pugasankara.com.

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