2011 Technology Roundtable: Putting data into context

The results of our 2011 Software Users Survey revealed that even though logistics professionals are taking a more calculated approach to vendor and product selection, they’re finally ready to turn up the spending—welcome relief for over-burdened users across the supply chain who are still toiling on outdated systems.

While our research team found the improved-spending data refreshing, we also learned that many logistics professionals are showing renewed interest in achieving a better understanding of the data that supply chain software systems are capable of churning out. In an effort to help shippers put this data into better context, we’ve gathered a few of the top supply chain software analysts who are closely watching the progress of supply chain visibility, business intelligence (BI), advanced analytics, as well as the steady evolution of today’s warehouse management systems (WMS).

Leading off this year is Shanton Wilcox, principal of supply chain management at Capgemini Consulting, who will explore the often-misunderstood concept of supply chain visibility. Jerry O’Dwyer, U.S. sourcing and procurement leader for Deloitte Consulting, then joins us to explain the growing importance of BI and analytics in logistics management. Greg Aimi, director of supply chain research at Gartner, will wrap things up this year by giving readers an update on the new capabilities WMS vendors are adding to these mature systems.

VISIBILITY: The Holy Grail
Logistics Management: In a recent survey of supply chain professionals your organization just conducted, 45 percent of the respondents said that supply chain visibility projects would be a main focus area for the coming year. What kinds of projects fall into that category?

Shanton Wilcox: Visibility is a very misunderstood term, in many ways it’s similar to the many interpretations of supply chain. From my perspective, visibility spans a continuum, from general or less mature visibility, to state-of-the-art visibility. Simple electronic information integrated between trading partners counts as simple visibility, as systems are directly connected. At the other end of the continuum are the visibility platforms that directly update based on order or shipment status, real-time across several trading partners, providing proactive exception-based management capabilities.

LM: Can you give us an example of how improved visibility might help logistics and supply chain professionals better manage the challenge of market volatility?

Wilcox: If you consider the more advanced form of visibility, shippers can proactively direct in-transit shipments to markets where products are moving at a higher velocity. Or manufacturers can determine what parts or materials are actually being shipped in the event of a catastrophe and re-plan manufacturing based on actual in-transit parts and materials. So, advanced forms of visibility allow partners to more efficiently execute management decisions based on real information, reducing latency and costs.

LM: What’s technology’s role in improving visibility? Is there a single solution that shippers can install to gain these benefits?

Wilcox: As is the case with all situations that drive significant value, there is no silver bullet, but it is achievable. Advanced visibility is complicated by distance as supply chains were extended globally and by the number of partners added to operations to drive efficiency and competitive advantage. So, many factors have to be aligned to achieve advanced visibility, and it starts with roles and responsibilities enforced with contracts.

It ends and materializes via visibility platforms, and many are commercially available that integrate the information flows in a business context that facilitate the definition of alerts and subsequent identification of exceptions. Without exception-based management governing visibility, the amount of information flowing between global partners would be too great for organizations to manage; so, technology serves as the unifying mechanism.

LM: What are the early steps logistics professionals need to take to get started in putting the right software into place?

Wilcox: As in most situations that involve the extended supply chain, look to partners that may be more advanced or experienced. It could be a supplier that gains experience from a different trading network or a logistics service provider that provides the capability to other partners. And when all else fails, read. There is a lot of information available regarding visibility and potential solutions.

LM: Where do you see visibility-enabling software heading going in the next 10 years?

Wilcox: Ten years from now, advanced visibility is going to be a “must have.” Companies are beginning to co-mingle freight on the same shipment. Supply chains will be become more virtual, with contract manufacturers all over the world shipping directly to customers. So, in this case, visibility will be required to operate in the future.

Picture a remote call center literally anywhere in the world taking a customer order over the phone; the order is transmitted to the OEM and the contract manufacturer simultaneously; the order is manufactured anywhere in the world; and upon completion it’s dropped shipped directly to the customer. In this situation, visibility technology will allow the customer to monitor the status of the order on-line and will allow the customer service representative to update the customer should anything change or require further attention.

ADVANCED ANALYTICS EXPLAINED
LM: In a recent article for our sister publication Supply Chain Management Review, you go into terrific detail in defining “advanced supply chain analytics.” Can you offer us your “elevator pitch” version of this concept?

Jerry O’Dwyer: Advanced supply chain analytics represents an operational shift away from management models built on responding to data. Emerging capabilities in this area seek to introduce a proactive management model, equipping supply chain professionals with the ability to continually sense and respond as business changes around them.

Moreover, advanced supply chain analytics can help supply chain professionals analyze increasingly larger sets of data using demonstrated and tested analytical and mathematical techniques, thus allowing them to spot patterns and correlations that may have been missed in the past.

LM: How does this advanced level of analytics differ from some of the statistical BI that many of the more sophisticated logistics and supply chain organizations have been putting to use over the past few years?

O’Dwyer: The biggest difference between pure-play analytics and advanced analytics we talk about is the level of complexity that can be simultaneously dealt with. Traditional analytics models include BI and statistical models addressing specific problems. But, those tools essentially provide outputs that require further interpretation to help leaders make meaningful business decisions. The success of traditional models was very dependent on the advisory expertise involved.

Advanced supply chain analytics can enable users to simultaneously factor in a host of problems and provide BI that involves synthesizing real-time data into meaningful information. It also includes a host of toolkits designed to address multiple problems that could potentially impact each other, providing a holistic solution.

LM: In terms of logistics and transportation management, can you share a brief example of what advanced supply chain analytics would act like in the context of day-to-day operations?

O’Dwyer: Advanced analytics seeks to take logistics decision support to the next level. Consider international container shipping. Oil prices are rising, capacity is constrained, and transit times are longer due to carriers’ slow steaming. Providing your carrier partners with accurate forecasts is key; however, it’s also typically very challenging.

Advanced analytics are designed to help you go further upstream, looking at demand patterns, forecasts, manufacturing schedules—even seasonality—to model your shipping requirements with more precision. The output is typically a more accurate capacity forecast that you can share with your carriers to secure capacity and make sure your shipments aren’t held up. 

LM: How does a logistics and supply chain organization take steps to implement this concept?

O’Dwyer: To implement advanced analytics, companies can start with the following three steps. First, develop a well-defined vision for advanced analytics so your organization knows what to expect out of its development. Once goals are set, a clear implementation plan should be set. Then, individual analytics efforts could be prioritized depending on the ROI and the criticality of the application.

Finally, from a people perspective, many supply chain organizations don’t have enough business experts with functional knowledge of different supply chain areas. Finding this diversity and breadth of experience is important, as is emphasizing analytical competency and expectation in the hiring and promotion process. In addition, companies should not ignore the IT skills challenge.

LM: What technology is involved?

O’Dwyer: A range of technologies can serve as the underpinning for the next generation of supply chain analytics. Many of these solutions are beginning to enter the market today or are already used by more innovative companies, albeit in select supply chain areas. The fundamental change is not necessarily to the types of analytics performed, though that will continue to evolve. Rather, the fundamental change is to the quantity, frequency, and types of information analyzed and how it is shared. Perhaps one of the most significant emerging and continually evolving relevant technology is a next-generation business intelligence and self-structuring data logic that can bring together different datasets, putting data into a context to enable rapid insight.

These new business intelligence and self-structuring data logic applications will allow users to ask questions of data constantly—as opposed to a weekly, quarterly or yearly basis. In the future, logistics and supply chain managers will ask questions of their own advanced analytics tools rather than the IT department facilitating a data-warehousing-led information hunt.

LM: For the logistics and transportation management function, what would you say is the greatest benefit?

O’Dwyer: The greatest benefit for the logistics management function is the forward-looking view and, in turn, the competitive advantage that advanced analytics can provide. For instance, if you’re trying to solve a network strategy problem, you want to keep material flowing through your supply chain from manufacturing plants to datacenters, and ultimately to customers in a cost-effective way that adheres to required service levels.

Traditional analytical tools could allow a user to optimize on a fixed set of variables, like number of plant locations, warehouses, demand centers and carrier-mix. However, they may not support the next level of decision-making determining a flow-path strategy to drive network configuration decisions. This is where advanced analytics helps organizations to provide enhanced support to logistics managers.

THE NEW ROLE OF WMS
LM: Many WMS vendors are adding new flair to these “mature” systems. What new capabilities should logistics professionals put to use?

Greg Aimi: There are four areas I would call out pertaining to more recent advancements over basic WMS. First, the mobile input devices for recording activities and inventory moves have a lot going on. We’ve long had RF hand-helds for scanning barcodes, but now we’re seeing the movement to voice, RFID, and more complex coding gaining momentum. Also, the mobile devices themselves are getting smaller and more capable, and there seems to be some convergence going on with smartphones and other mobile devices. 

Second, we’ve seen a pretty dramatic increase in the use of labor benchmarking systems for comparing task performance and obtaining higher levels of productivity of the worker. Third, we’re seeing a growth in the use of robotics with “smart” vehicles from the likes of Kiva and Seegrid that introduce significant change in certain warehouse environments where they make sense over heavy automation. And fourth, we’ve certainly seen a rise in collaboration with suppliers and carriers to coordinate dock-door schedules with the yard and with internal workers.

LM: Last year we discussed the move by WMS vendors toward Software as a Service (SaaS) and the broader, greater cloud. How has that progressed?

Aimi: Our research estimates that in the next five years spending on SaaS-based applications in supply chain execution will grow from around 12 percent today to over 18 percent. While there are new entrants to the pure SaaS WMS arena, which accordingly have light to basic capabilities, there are also a couple of vendors that have more sophisticated and robust WMS solutions than the market is probably aware of.

At the same time, the major independent software vendors of WMS are beginning to offer a hosted version of their traditional applications hosted in the cloud. This requires a change in the pricing model to convert it to an “expense or fee” that has perplexed some of the larger companies that depend on the big upfront license fees for their revenue structure.

LM: What type of operation is the best fit for a SaaS solution?

Aimi: There are a number of warehouses and depots that carry inventory for which the Tier-1 WMS solutions are simply overkill. The basic capability SaaS would be appropriate for these environments both from a capabilities standpoint and a cost perspective.

LM: It seems that industry jargon freely uses “cloud” and “SaaS” interchangeably. Is that safe to do when discussing WMS delivery?

Aimi: I think it’s important to distinguish “cloud” from SaaS WMS. A few of the SaaS WMS solutions are quite new and the features and functions are correspondingly light compared to the existing, on-premise Tier-1 and Tier-2 solutions. Moreover, if widespread adoption occurred I would imagine the SaaS environments being challenged to handled the throughput—granted this would be a short-term complication.

Cloud WMS can be one of the more capable solutions—a single private instance—hosted on behalf of the customer by a cloud service provider. This environment would be as capable as any on premise deployment, except the IT environment and management would be outsourced. 

LM: Our 2011 Software Users Survey found that 35 percent of respondents say they’re ready to upgrade or dive into a new WMS. What steps do you suggest they take?

Aimi: The WMS market is mature. There’s such parity in core WMS capabilities across the leading product offerings, which makes other criteria, like breadth, depth, technical architecture, company stability, and service reputation critical for differentiating solutions. Technical architecture is now a more important evaluation criterion as componentized architectures like SOA are prevalent and can prevent the traditional challenge of one-off customizations.

WMS is moving beyond just process execution, with more emphasis on adding value through better intelligence and decision making; so, it’s time to move technical architecture higher on the list of evaluation criteria. Make it second only to functionality. Matching proven implementations with the processes you need to support is a best practice. This doesn’t necessarily mean they have to have customers in your same industry, but the internal processes supported or required should be the same. Focus as much time on investigating support for enhanced decision-making as you will on process and activity execution.

LM: Gartner writes about understanding warehouse complexity before moving into this assessment. What should warehouse/DC managers take into consideration when going through this exercise?

Aimi: Most companies operate multiple facilities if not multiple supply chains. Complexity may be different at each facility or across different businesses. More complex facilities require more functional breadth and depth to support their needs, while less complex operations often require less functional robustness.

However, the problem with terms like complexity is that many users say, “I’ll know it when I see it.” But, defining it is much more difficult. This vagueness is especially unacceptable when selecting new WMS applications if complexity is a strong indicator of the functional requirements.