Business Strategy Common Business KPI types Warehouse Strategy
Financial Health Profitability Liquidity Inventory Turnover Return on Assets Reduce Costs: per period, per volume, or per order
Governance CSR, ESG and DEI Structure & Accountability Resilience & Continuity Audit Accuracy Expand Reporting, Improve Safety & Sustainability
Growth Customer Acquisition Cost Sales Revenue Brand Awareness Headcount & Asset Value Free Up Capacity, Be Ready to Scale
Process & System Performance Productivity & Waste Project Success Rate Output Quality Capability Adopt New Technology and Build Digital Maturity
Customer Satisfaction Churn Rate Net Promoter Score Customer Lifetime Value Perfect Order Rate Ship faster, in full and with thorough documentation
Culture & Effectiveness Employee Retention Participation & Satisfaction Profit per Employee Performance of Individuals Improve employee quality of life and learning opportunities.

How to get around the limitations of your WMS

January 17, 2024
Joe Fitzpatrick

The effects of the covid-19 pandemic have demonstrated some glaring vulnerabilities in global logistics. Many executives outside the operational realm had simply assumed that existing technology would be good enough to facilitate rational decision-making that could take into account what’s happening at every point along the supply chain, including in a crisis.

In reality, most operational decision-makers have little visibility outside their own domains. Even that can be somewhat lacking. As with many areas of business over the last decade, a certain level of technical capability exists theoretically, but does not exist in practice.

The supply chains of the near-future will demand the seamless transfer of information between customers, shippers, carriers, and each node in between.

But for now, most companies have to take care of warehouse management with incomplete data and inflexible software, “largely making compromises between the way a warehouse wants to work and the way the system allows the warehouse to work,” as researchers from the Rotterdam School of Management in Europe warned in 2002. “In certain environments, such compromises might seriously degrade warehouse performance.” ¹

Two decades later, the situation has not changed much.

A modern WMS is an impressive feat of computer science, bringing together multiple types of user interface with some heavy processing - in the best packages even predictive analytics - behind the scenes. But it’s also the case that the richer a suite of software, the harder it is to change.

In Warehouse & Distribution Science, professors from the Georgia Institute of Technology observed that:

“The working life of a warehouse management system is generally greater than that of the computer language in which it was written. Consequently, most WMS’s in current use are an accretion of many different computer languages… This can make them hard to maintain or customize.” ²

Ed Frazelle, The founder of Georgia Tech’s logistics institute, goes even further and says that warehouses today are expected to do more than ever but have “less warehouse management system capability,” than before, arguing that this is “a by-product of Y2K investments in enterprise resource planning systems.” ³

For some companies, this probably feels like being stuck between a rock and a hard place. Make do with a system that’s less fit-for-purpose with each passing day, or take a risk on another significant technology investment that might end up having an even shorter life cycle?

The answer lies in fundamentally rethinking how operational software ought to be procured and installed.

In the 90s, the all-in-one package model of line-of-business applications made sense for the buyer as well as the vendor. Today it only makes sense for the vendor.

New programming paradigms and business models in the software space, enabled in part by smaller chips and faster, more prolific internet connections, have transformed the incentive structures that fuel innovation. The result is that value, both on the simple level of functionality and usability, and on the more strategic level of investment lifecycles and extendability, is today more readily found when purchasing smaller applications that do one thing and do it well.

One of the gamechangers that allowed companies like Amazon and Alibaba to be so explosively successful is the progress that Application Programming Interfaces (APIs) have made, which allow multiple pieces of software to communicate with each other even if they’ve been developed in isolation.

Today it’s quite straightforward to plumb together multiple pieces of specialised software, each of which performs a specific function to an excellent standard, resulting in a systems architecture that provides precisely the features the organization requires, behind interfaces that are tailored to each user’s needs.

Furthermore, vendors of such software are sometimes willing to include a lot of assistance in configuring these systems, or even to develop custom features or integrations at affordable rates. It’s no exaggeration to say that the business model of this type of vendor hinges more on customer success than that of previous generations of technology companies, which tend to aim for customer captivity.

The Dutch researchers in 2002 suggested that rather than be trapped by a warehouse management system that rapidly depreciates in value while forcing the warehouse to operate on the software’s terms, it “seems better to implement a tailor-made WMS.”

Of course, they knew at the time that this was easier said than done for most organizations. In 2002, such a project would be prohibitively expensive and full of risks compared to a plentiful marketplace of ‘good enough’ off-the-shelf options.

But today, a tailor-made WMS doesn’t have to be something built from the ground-up. Rather, it can be assembled from a basic, mid-market or high-performing niche WMS as a base, customised and configured with the help of the vendor and extended with specialised functionality from third parties.

And this is precisely how the most tech-savvy organizations seek competitive advantage.

In cases where moving away from a legacy WMS is not possible, its shortcomings can still be addressed by smart integrations, earning the warehouse breathing room in the medium-term.

To offer a concrete example, receiving operations account for about 17% of total warehouse costs on average, as reported in Introduction to Logistics Systems Planning and Control. Furthermore, these processes are “difficult to automate and often turn out to be labour-intensive.”

Meanwhile, Frazelle paints us a picture of how a world-class warehouse receives material:

“The personnel and equipment required to unload each inbound warehouse load should be optimally prescheduled to eliminate the possibilities of delays and/or dock congestion.”

Such resource coordination is something at which leading-edge warehouse management systems excel. There’s just one problem. How can any of this be optimized if the contents and time of arrival of shipments can’t be predicted?

“balancing the use of receiving resources — dock doors, personnel, staging space, and material-handling equipment — requires the ability to schedule carriers and to shift time-consuming receipts to off-peak hours…”

In other words, the efficiency of a warehouse’s receiving operations is limited by the quality of its communications with external carriers.

It’s true that many of the more expensive WMS’s include some form of dock scheduling. But not one of them has tackled the problem with much care or depth. Indeed, the warehouse management systems that focus specifically on what happens inside the warehouse tend to perform best.

A solution like DataDocks tackles load scheduling directly, taking into account the relationship component intrinsic to bringing about behavior change from customers, carriers or suppliers.

Dock scheduling is a way to free up resources and establish better control over warehouse operations in general. It serves as the crucial missing link in information transfer between systems, connecting transportation with warehousing and bringing logistics management closer to end-to-end visibility.

For warehouse managers, it represents a natural first step in overcoming the limitations of warehouse management systems.

Bibliography
  1. Faber, Nynke, and Steef L. Van de Velde. "Linking warehouse complexity to warehouse planning and control structure: an exploratory study of the use of warehouse management information systems." International Journal of Physical Distribution & Logistics Management (2002), pg. 381
  2. Bartholdi, John J., and Steven T. Hackman. “Warehouse & Distribution Science”: Release 0.98.1. Atlanta: The Supply Chain and Logistics Institute, 2019, pg. 36
  3. Frazelle, Edward H. World-class warehousing and material handling. McGraw-Hill Education, 2016, pg. 14
  4. “Linking warehouse complexity" pg. 381
  5. Ghiani, Gianpaolo, Gilbert Laporte & Roberto Musmanno, Introduction to Logistics Systems Planning and Control. John Wiley & Sons, 2004, pg. 159
  6. Frazelle, pg. 121-122

let us help you decide if datadocks is a good

fit for your needs

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.