Logistics Viewpoints just published an article I wrote called "You can't really count on cycle counting methods.” After talking to several organizations, I learned they all deal with an inventory reconciliation problem. Please feel free to add to the conversation or let me know what you think.
Whether we like it or not, every company on the planet with any significant supply chain operation has an inventory reconciliation problem, even those relying on cycle counting methods. It doesn’t matter if you are a retailer, manufacturer or logistics service provider, or if you have the latest and greatest warehouse management system. The fact is, if humans have to physically touch or scan inventory or conduct inventory checks or processes, then errors will occur. The only question is the size and scale of the problem.
All organizations tend to deal with this problem at some point or another. As you can imagine, there is a broad array of approaches taken and process maturity across companies. Some never check, some shutdown operations to do a full check, and others have a robust approach to cycle counting. In the best case scenario, you have a process with 95% to 99% cycle count accuracy. Why not 100%? Just to reiterate, you may have the best warehouse staff on the planet, but if they are following manual repetitive tasks, errors will unfortunately occur.
Industry leading companies are now looking into autonomous UAS (Unmanned Aircraft System) technology or drones. Coupling it with advanced sensors capabilities, including passive-RFID, optical, and barcode may significantly improve the operational effectiveness and efficiency of inventory checks in yards, lots, and inside of warehouses. Elevating the sensor platform into the air with the use of an autonomous UAS enables automatic, accurate, efficient, and safe inventory checks in hard to reach locations.
This technology is very much in beta mode in a number of supply chain environments. If you don’t have an initiative looking at drones, you are behind your competitors. There are many large corporations that are absolutely working on this, and there are others that have not even started and are still relying on cycle counting methods. So if you fall in the latter category, you are going to have some problems ahead of you.
Everyone else’s margin is your opportunity. If you are not focusing on making your supply chain better, faster, and cheaper, then you have a problem on your hands. Take manual repetitive tasks and the low cycle count accuracy that comes with it and put it in the arms of an autonomous robot. Doing so will provide you with a significant return, especially if you are operating at scale. Remember, if you’re not doing anything right now, or even talking about it \, your competitors are. Period.
I don’t want to come across as flippant, but the ideal timeframe to start looking at this was six to 12 months ago. The reality is that this technology is moving faster than Moore’s Law is in the semiconductor business. You just need to look at the amount of money being pumped into the drone business, the number of use-case applications, the number of companies that are looking at adopting it, and the advances and cost performance of all the technology related to it. It is moving so much faster than any other technology that I am aware of.
In terms of a pilot in the way that companies have engaged us, they say, “Here are our problems. Is this something that is a near-term opportunity for this type of technology?” Invariably that means us going out, taking a look at the facility, collaborating on the potential key-use cases, and then putting together a proof-of-concept to show a value that is higher than cycle counting methods. There’s no point in introducing a technology that brings more burden and more cost structure. This needs to radically change and shift the way companies are operating today. If it is not going to have that impact, you are wasting your time and you should move on to another use-case in your organization. There is undoubtedly an application in your organization that is going to have the biggest return, and we want to find that.
We have been thoughtful in our approach to focus on specific areas that we are good at, and with our experience, we can now quickly and efficiently identify who benefits with this strategy. For instance, those with a 10,000 sq. ft. warehouse may not need to utilize this plan at the moment, but those with a 1,000,000 sq. ft. distribution center can generate significant value.
Why should we care?
It all boils down to the customer experience. I know how frustrated I get when I try to buy a product online and the retailer doesn’t know for sure if the item is in stock or it cannot deliver it in a timely fashion. This even happens with well-known retailers. Consumers want retailers to set reasonable expectations and consistently meet them.
If a retailer has 100 distribution centers, each carrying $25M worth of inventory, with a 1% inventory error rate and relatively low, you can imagine the scale of ambiguity and exposure that would persist around inventory items across its distribution network.
The #1 reason why organizations care is inventory accuracy, and the race to 100% cycle count accuracy exists across all omni-channel organizations.
What are the potential solutions to this problem?
I touched on a potential approach in a previous blog post regarding the Four Stages in Digital Disruption, which in the context of cycle counting methods would mean:
Managed: How does my warehouse management system (WMS) prioritize and manage my process of dealing with inventory?
Assisted: How does the use of barcode/RFID scanners, wearables and other technology enable warehouse operators do their job more consistently?
Automated: What autonomous robots exist for the purpose of checking inventory at the frequency I prefer?
Optimized: What technology exists to provide greater insight into inventory levels, position, movement, etc. with the real-time data received from autonomous robots?
Interestingly enough, organizations that are approaching me for help with #3 and #4 already have significant competence in #1 and #2. But because #1 and #2 still depend heavily on humans, they are still falling short on their inventory level confidence.
By passing the job of cycle counting methods to an autonomous robot, organizations now have an enabler to get to the 100% confidence goal they are trying to achieve. For example, as reported by Reuters a few months ago, Walmart is 6-9 months from using drones to check warehouse inventory. According to the article, “drones can reduce the labor intensive process of checking stocks around the warehouse to one day, [which] currently takes a month to finish manually.”