WAREHOUSE MATURITY MODEL PHASE 5: IT’S TIME TO BECOME MORE PROACTIVE WITH PERFORMANCE IMPROVEMENTS

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Partner Blog

by: Mark Wheeler / Zebra

THROUGH THE MORE FOCUSED UTILIZATION OF INTELLIGENCE TOOLS, YOU CAN CREATE A “CRYSTAL BALL” THAT HELPS YOU PREDICT WHAT MAY BE COMING BASED ON CURRENT TRENDS AND ADAPT OPERATIONS IN AN OPPORTUNISTIC MANNER.

When a disruptive force sweeps the supply chain, you have no choice but to react. Yet, letting others consistently dictate your pace of operations reduces the control you retain and your ability to better manage the dynamic impacts on your business, partners and customers.

That’s why all warehouse operators stand to gain from predictive capabilities. When you can see what’s coming, you can proactively adapt processes and systems to withstand the impact. You can also prepare your people. Trying to adopt new technology tools and overhaul workflows in the middle of a chaotic situation is a band aid at best. At worst, such an effort could prove even more disruptive. And trying to increase procurement volumes after a tidal wave of demand rolls in won’t necessarily help you avoid an inventory shortage. You will still experience fulfillment delays while waiting for the time items come in, assuming you can even secure them.

Therefore, the concentration in Phase Five of Zebra’s Warehouse Maturity Model remains squarely on gaining foresight that allows for proactive operational improvements.

WHAT TO EXPECT IN THE FINAL PHASE OF YOUR MODERNIZATION JOURNEY

In the first three phases of maturation, you are typically focused on increasing and optimizing the use of mobility solutions in all operational areas, tracking every inventory move using transactional data capture, and leveraging targeted automated data capture that gives visibility into processes lacking it. In Phase Four, you are able to gain insight into the real-time location of assets and people in motion by automating processes that can and should be automated.

So, by the time you enter Phase Five, the actions of workers will be based on a large, complex set of operational information that can either eliminate disruptive waste, errors and congestion, or contribute to it. These insights, if properly applied, can also help increase safety, profitability and efficiency. That’s why the goal in this final phase is to better analyze and utilize the data captured to more proactively enact changes for operational improvement.

Though some level of reactivity will always be necessary (we don’t know for certain what the future holds), it is possible to conduct a deeper, more accurate predictive analysis of operational performance to anticipate and prepare for potentially disruptive incidents. This is done by:

  • fusing multiple external and internal data sources.
  • implementing real-time sensing pervasively throughout operations.
  • continuing to extend visibility to people, assets and materials.
  • building execution systems that leverage machine learning and artificial intelligence (AI) to remove as much human-initiated decision making as possible and allow for more real-time prescriptive analysis and business adaptation.

When you are able to look deep into all your workflows as well as operations occurring beyond your four walls, it becomes easy to work harmoniously with your supply chain partners and better adapt to issues stemming at their facilities. In fact, gaining an outside-in perspective is key to eliminating the silos and fragmented decision making that create bottlenecks and disruptions in the broader supply chain.

Also important is the ability to automate complex, multi-variate decisions related to a number of assets, including inventory, equipment and even people. You cannot rely on static business rules that are reviewed and updated on a quarterly basis (at best) if you hope to maintain a more resilient operation capable of mitigating issues and maximizing opportunities. Nor can you ignore the health and performance of your mobile devices given how much they dictate worker productivity and efficiency. My colleague Matt Rance just spoke about this in detail in a blog post last month.

That’s why you won’t enter Phase Five until you have an environment that includes a best-in-class mobility strategy for front-line workers in addition to sensor-based devices that capture location data and other properties and conditions of assets. You must also have the right AI and machine learning solutions in place to fuse data from multiple sensors and generate the operational insights required to achieve predictive and adaptive operations. It’s the only way to maintain full visibility into – and accountability for – your operational performance and the influence it has on supply chain partners and customers.

CREATING YOUR “CRYSTAL BALL”

Warehouse management and control systems have the ability to adapt and change as conditions evolve – as do workers, assuming they have reliable devices in hand that can deliver real-time guidance. But you will only be able to provide front-line workers with real-time instructions on how to avert issues and improve outcomes if you can couple the more vigorous external performance analysis with an intelligent behind-the-scenes analysis of the complex data sets captured within your four walls.

So, expect to break new ground with the hardware, software, sensors, real-time location systems (RTLS) and intelligent edge solutions introduced in phases one through four and likely expand your existing architecture to include additional types of sensors, devices and automation platforms. Also be prepared to leverage new types of software solutions and services to extract even more insights from the valuable transactional and real-time data collected and stored in your various systems, including device-centric performance metrics.

For example, Phase Five is when you can expect to fuse data from radio frequency identification (RFID), weight sensors on the forks of a lift truck, temperature sensors on cartons or goods, machine vision or computer vision, and an app that references barcode intelligence and product recalls to make real-time decisions about inbound goods. If any of the criteria aren’t met according to the algorithms set up, the goods can be rejected without ever receiving them into the warehouse. This is especially helpful if it is a consumer safety risk, as this will ensure goods never get into circulation.

Behind the scenes, an intelligent automation solution will likely be making other key decisions about the quality of goods based on algorithms that tell it what to look for:

  • Does the weight match the weight of the goods provided on the advance ship notice? Is it lighter? If so, something could be missing.
  • Did the product stay within a safe temperature range the whole trip to the distribution center?
  • Do the machine vision cameras, fixed industrial scanners, and/or computer vision technologies detect a carton missing, missing label or anything out of the ordinary?
  • Do the package dimensions on the barcode intelligence correlate with the shipping system?
  • Did the right quantity arrive on the pallet?

In fact, Phase Five will likely be the point at which industrial automation solutions such as fixed industrial scanners and machine vision cameras become pervasive. Workers must be able to quickly determine the condition of both inbound and outbound assets in real time, but the human eye can’t catch everything. At the same time, workers can’t be everywhere at once. So, it’s critical at this stage to transition to more intelligent workforce management tools to optimize labor scheduling and utilization.

Just know that it will be difficult to strike the right labor balance without first capturing and understanding the physical moves, transactions, conditions and attributes of assets and processes. That’s why we always help our customers integrate their physical operations with enterprise systems once ready to enter Phase Five. Once each component has visibility into the other, it becomes even easier to orchestrate operations as business needs evolve.

The best place to start is by revisiting key performance indicators, goals and outcomes defined in the other phases. Then consider the relationship between your enterprise systems such as the warehouse management system, transportation and yard management systems, enterprise resource planning (ERP) system and your physical operations in the context of the current climate. For example:

  • How can you use automated inventory control sensors to keep the warehouse in-sync with available-to-promise inventory positions to better manage inventory?
  • Is there a way to sync processes and priorities within the facility to meet cut times and transportation asset capacity constraints using existing transportation systems?
  • How can customer service systems be optimized to provide accurate order status, which is key to both improving fulfillment capabilities and addressing customer inquiries?

From there, you can begin to consider the data sets you do not already have access to that can inform decisions for the challenges you are trying to solve. For example, is there a way you could access a supply chain partner’s transportation system to have live updates for shipping status? This would allow your team to know if a shipment is going to be late – or arrive early – so it can plan accordingly and reallocate resources if needed. You can pair that information with internal employee scheduling and yard management systems to ensure there is a clear dock door and sufficient receiving staff on the dock when the order comes in. Of course, it would be best if you had a variety of sensors and machine learning solutions in place at the dock to achieve a no-touch receiving process when the pallets arrive so precious time is not lost.

Remember, this is also valuable information for a plant that is waiting for an important part for assembly, or a retail distribution center waiting for inventory from a third-party supplier during a peak holiday rush. And industry collaboration among vendors opens the door to frictionless supply chain operations. The more data the better – and the more real-time data, even better. Setting up a plan for secure data sharing as part of your data pool to optimize operations will be an excellent way to acquire more meaningful data insights. I also recommend you use application programming interfaces (APIs) to create custom applications that enable you to access third-party database insights, such as weather, traffic and more. Fusing this data with your own edge and enterprise data will enhance decision making, save time and generate more universal data that can be shared across the supply chain to solve sustained and emerging challenges.

ARE YOU REALLY READY TO MOVE INTO PHASE FIVE? TWO WAYS YOU’LL KNOW

I realize Phase Five is very future-facing, and you may not be ready yet for these types of solutions. Only a few warehouse operations have matured enough to warrant further investment in AI, machine learning and other intelligence platforms at the scale dictated by Phase Five implementations. And only one in five decisions makers surveyed for Zebra’s Warehousing 2024 Vision Study ranked operating with data-driven performance and real-time guidance and decision an important operational outcome in the next few years. However, things are evolving quickly, and it will not be long before predictive analysis and proactive performance improvements will be a necessity – and reality – for everyone.

You’ll know you’re ready to take the leap forward when:

you begin experiencing challenges best served by incorporating more diverse data into automated decision making. Remember, the real-time data you currently rely on is primarily location based, and even more of the data available in your systems is probably underutilized. It’s likely you are still performing a lot of human-initiated data interpretation that is not holistic or real time, which leaves you with incomplete information – and unable to work proactively. In Phase Five, you will gain the tools needed to extract, predictively analyze, and prescriptively apply the data across your operations.

and/or

you are still too reliant on business rules that can – and will – change. To fully mature, your warehouse operations need to become more reliant on algorithms that are able to fuse multiple sets of data together to make complex decisions in real time to optimize and error-proof workflows.

One more consideration: you will need resources for intelligent AI and machine learning-based app development as well as access to APIs. You don’t necessarily need them in house. You just need to ensure your technology partner can provide these tools and services as required.

HOW TO MEASURE SUCCESS IN PHASE FIVE

Though each warehouse operator will have a different set of key performance indicators (KPIs) depending on challenges and goals, you’ll know you are properly maturing in Phase Five if you are:

1.  Orchestrating warehouse systems with transportation, yard and other enterprise systems to ensure all those systems share or exchange information. As I noted before, this helps you anticipate disruptions or opportunities and respond with the best next move. However, it’s vital you also directly integrate each of these enterprise systems with the physical operations in the warehouse—beyond the location of assets—to proactively adapt to changing conditions and have a profitable, customer-centric organization. For example, consider the benefits of a purchasing manager’s ERP system being directly linked to the physical operations of the warehouse in this scenario:

A fixed RFID reader and a fixed Bluetooth® Internet of Things (IoT) bridge at the dock doors read the RFID tags and temperature sensors of an inbound pallet as the lift truck driver backs out of a trailer. The purchasing manager and the lift truck driver are immediately alerted that the perishable goods have been compromised in shipping and don’t meet the designated temperature. The purchasing manager contacts the supplier instantly and arranges for a replacement to be sent later that day, and the receiving manager is able to refuse the compromised goods. No precious time is lost.

2.  You are well connected with the people and systems collecting data outside your four walls. We know the supply chain is a complex network that can have a “domino effect.” One tiny delay can impact everyone up and down the line. Therefore, including real-time data from outside your warehouse’s four walls in your performance analysis is key to maintaining an adaptive operation. Sharing data – whether by participating in a blockchain/digital ledger that offers a verifiable chain of custody for goods or simply transmitting details about order status – is key to providing the answers you and your partners need to solve problems and keep your mutual customers happy.

3.  You have put your trust in data automation and machine-dictated decisionsThis may be the most challenging of all, as it’s not going to be easy to abandon tried and true methods of acting based on what is in front of you here and now. Going from an operation where humans play an integral role in interpreting data to letting AI and machine learning platforms access hundreds of thousands of real-time and transactional data points to predict what will happen is going to require some change management. And relying solely on those algorithms to determine the best next move based on an intelligent system’s prediction may seem unfathomable. But, with as fast as the supply chain moves, it is just not possible for a human to process the shear amount of data that is captured each minute, let alone in a day.

It’s far more impactful for humans to identify the data sources and processes AI and machine learning should use to constantly learn new patterns and, in turn, improve accuracy and prescribe actions that will optimize workflows, resource and labor planning, and even facility configuration. Just consider how many data points must be analyzed to improve utilization for the whole pool of pickers assigned to every shift, every day until an optimized workflow can be achieved: distance and route traveled, orders picked per hour, number of scans, order size, out-of-stocks encountered, location of picks, product type picked, dwell time, number of trips to packing stations, weight handled, device metrics, and much, much more.

Utilizing data points related to the location of picks, dwell time and picks per hour, an AI solution can instantly make the connection that pickers who are not encumbered with congestion from other pickers can pick more orders per hour and then suggest routes to pick locations that will keep pickers more productive. It can also trigger the need for cycle counting in a specific area if a high occurrence of out-of-stocks is encountered by pickers. Intelligent automation methods can quantify how pickers who have orders focused on a zone are able to pick more orders per hour and the WMS can begin to organize picks by zone.

IN OTHER WORDS

Your primary goal in Phase Five is to fuse together every piece of data collected at the edge of your operations – and across your entire supply chain – so you can better predict what’s coming, automate decision making, and become more proactive in your process and workflow improvements. Just remember that every piece of data is valuable, whether it is generated by a temperature sensor, weight sensor, machine vision camera, barcode scan, locationing beacon, device diagnostic tool, or an employee via a workforce management app. Proactively maintaining the health of your mobile computing, printing and scanning devices is key to boosting worker safety, efficiency and productivity. And taking employee feedback into account when setting schedules or assigning tasks will help to boost morale and well-being – which, in turn, boosts productivity. Though much of the decision making will be taken off their plate, they need to know they are still valued. Plus, improving labor utilization and providing detailed guidance on what to do every second of the day makes workers’ jobs easier, which helps them get more done and, in turn, increases their value.

If these goals feel unrealistic for your operation, know that maturation is meant to be gradual. You may not be ready yet to enter Phase Five, and that’s okay. When you are, the Zebra team will be here to answer your questions, help you map out a technology strategy, and guide you through the implementation and optimization process. We even have a team of consultants who are experts in change management and can provide you with a set of tools and best practices designed to minimize disruption as new technologies are integrated and workflows evolve.

Feel free to contact us whenever you’re ready. Of course, we are happy to support you through the other phases as well, so don’t hesitate to reach out.

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EDITOR’S NOTE:

This post outlines the final phase of Zebra’s Warehouse Maturity Model. If you missed Mark’s previous posts, you can catch up here:

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