The days of static supply chains, both globally and locally, are long gone. Enterprises now must deal with an immense level of complexity and volatility, with continual change being the new normal.

Organizations today have to grapple with faster product release cycles; shorter product lifecycles; omnichannel ordering, delivering and returns; the move into emerging markets; trade wars, and more. In addition, rising consumer expectations and increased demand for purchasing convenience, delivery speed, and product choice are increasing pressure for more responsive supply chains.

New business models for e-commerce and accompanying customer-service expectations are gaining traction. Almost all manufacturers of brand products that formerly relied on retail partners to peddle their products are nowadays expanding their direct-to-consumer (DTC) business, both online and via their own retail outlets. According to Forbes, in 2018 more than a third of consumers reported that they bought directly from the website of a brand manufacturer in the previous year.

Ineffective Traditional Warehouses

One node in supply chains that has traditionally been less flexible and adaptable is the warehouse and distribution center. This is especially true for those handling high volumes of bulk units, which have tended to have rigid automation capabilities. Historically, warehouses and DCs have been designed as storage and delivery facilities for large bulk quantities, with wave picking being the most efficient way to process orders. The main shortcomings of wave picking is that items are processed in a serial manner, and it’s not easy to add similar work or additional items to a wave that is already in progress.

Needless to say, traditional high-volume warehouses have not been designed to handle small DTC orders. Because those traditional DCs were built well before today’s mixture of e-commerce orders and related shipping, companies have coped with low-volume DTC orders by building secondary facilities or dedicated areas in the main warehouse (e.g., so-called put walls). In fact, every retail store is now a warehouse of sorts, including pickup-return lockers. Needless to say, these separate dedicated areas carry significant additional cost due to redundant equipment, inventory, and labor.

While technology for DC automation and task execution has long existed, it is inadequate for today’s needs of speed and agility. Warehouse management system (WMS) software has allowed little if any visibility into and control of a case or pallet once the item has been inducted into a conveyor system.

On the other hand, the traditional warehouse execution system (WES) software had absolutely no perspective of anything outside of its world. Consider that an inbound shipment is late, and some goods are needed right away at the loading dock or pick station. WES software would not allow visibility into that; hence nothing would be done to expedite the shipment. Likewise, if there’s a sudden change in demand and the product on the conveyor, for example, is needed elsewhere, one would have to let the original plan run its course, reverse whatever action was taken, then start the new fulfillment process using the WMS software.

The bottom line is one would have the two biggest software components of the warehouse, WMS and WES, talking to each other via a telegraph of sorts. But because they’re independent and unaware of one another, truly holistic decisions (and intelligent ones made in near real time) are nearly impossible. This lack of collaboration is exacerbated by the fact that in most cases both systems are made by different vendors, use a variety of languages, terminologies and the like.

Amazon-izing the Warehouse

But in these days of internet-of-things (IoT) connectivity and micro-services enabling easier and more open integrations, isn't it much easier for the WMS, warehouse control system (WCS), and WES software components to talk to one another in near real time? In other words, wouldn’t the integration between WMS, WCS, and WES help with the omnichannel one-day deliveries of Amazon?

It appears so. This multi-system integration helps companies adapt and respond more quickly. To deal with the Amazon effect, companies need to increase warehouse throughput, then respond quickly when orders drop (or any other changes occur).

So yes, an orange that was squeezed dry a few years ago (the traditional warehouse) now seems to have more juice left (especially when one throws new robots into the mix). It’s not unusual for a single DC to use multiple brands and types of automation and robotics. There’s a need for the increasingly sophisticated integration of disparate technologies so that they can work together, and with the human workforce, to better anticipate the workload needed from the overall WMS software. It’s important to have robots and automation equipment connected to a really good brain. That is, DCs need the warehouse intelligence to efficiently orchestrate workflows across the full spectrum of human and machine resources.

Modern WMS systems must now enable better fulfillment execution capabilities for retailers, distributors, and other logistics companies. For this, the software needs to allow for improved order flexibility and asset use, as well as expanded warehouse workflows via mobile devices. Modern warehousing solutions need to espouse new order intelligence and optimization capabilities, as well as the orchestration of humans and machines to increase agility and efficiency. Modern WES software must drive value not only in fully automated DCs, but also in manual and hybrid automation environments.

In addition, warehouse supervisors need to be able to view, diagnose, and address issues from any location. For this, they require the software to have a responsive and intuitive touchscreen user interface that leverages modern data visualization techniques. Managers also need to use advanced analytics to assess the performance of the warehouse overall, and to gain insights and responses to trends or issues in near-real time. In addition, warehouse associates need to be able to use the new screens to streamline the completion of different tasks, and reduce training times.

Manhattan Associates recently introduced its order-streaming capabilities to produce an intelligent fulfillment optimization engine that’s capable of simultaneously processing wave, waveless (e.g., a single order, batch, zone, etc.), and flow-through orders in a single facility. Order streaming uses machine learning to orchestrate activities between the warehouse workforce and automation assets, thereby dynamically managing different fulfillment methods with higher service levels.

Simulation Helps Enhance Agility

Other WMS software vendors such as HighJump and Softeon also offer WES simulation capabilities. The software generates insights and data for analysis and decision-making over multiple time horizons. WES simulation enables the warehouse to analyze and understand digitally the performance and effect of any change that’s considered, without having to perform costly physical deployment, thereby improving the company’s decision-making and reducing risk.

Warehouse simulation can be used for process validation against documented expectations and other use cases. Simulation enables the testing of processes with minimal resources. Companies can also use it to test performance (throughput and response times) and conduct what-if analyses. For example, they can ask how changes to WMS software settings, such as adding put walls and turning on task interleaving, can affect throughput and productivity.

Astute WES software also needs to perform more tactical simulations to enable insight on a given day’s or shift’s order pool against the DC’s resource availability and constraints. This allows, for example, a company to understand early in the day or shift where it might have bottlenecks or resource constraints versus known or expected demand.

The solution also needs to anticipate and predict the next best steps to identify bottlenecks, ensure resource balance, perform a stress test for peak periods (e.g., Black Friday), conduct automatic storage and retrieval systems (ASRS) simulations, and evaluate the effects of incrementally adding new technologies. It must sense demand for DC resources in near-real time, reallocate people and equipment as needed, and potentially reroute some orders to meet the latest demand. Some WES simulation solutions can also help with gaining visibility into the site traffic for the yard, and evaluating picking strategies for each store or warehouse.

As we look to the future of self-healing (cognitive, self-driving, and adaptive) supply chains, warehouses will need to do their share of being adaptable. One should expect future world-class software vendors to blend WES, WCS, and WMS capabilities together, to enhance the adaptability and responsiveness of tomorrow’s supply chains.

PJ Jakovljevic is a principal analyst with Technology Evaluation Centers.