In-Depth

APS Technology: Powering Supply Chain Management

• 09/01/1999

Business-to-business e-commerce is approaching hyper-growth in the U.S. market. As early adopters of e-commerce have concentrated on "sell-side" commerce, linkages designed to address "buy-side" commerce and business planning collaboration are rapidly taking shape. Certainly, the front-end Internet marketplace is driving a huge share of this growth, but the back-end planning and fulfillment technologies are catching up fast.

The information technology that enables sharing of business plans across strategic links in a complex supply chain should strengthen product fulfillment between trading partners. If managed effectively, such technology can predict demand, optimize fulfillment resources enterprisewide and ensure that product is in the distribution channel when promised.

The market’s faith in e-commerce won’t come from a slick Web site. It will come from consistent delivery of the product the customer is expecting, when expected. Advanced Planning and Scheduling (APS) technology will play a powerful role in real-time commitment and order fulfillment strategies for those companies ready to take part in the new electronic marketplace.

Within the IT research community, analyst firms, such as GartnerGroup and AMR Research, have begun to classify APS software as a technology that encompasses a variety of planning and scheduling solutions. According to AMR, this technology segment grew 55 percent in 1998, and is on track for 58 percent growth for 1999.

All of the excitement around these software offerings begs the question, "What is APS?" The definition and competencies of APS-based applications have been developing for roughly 10 years. Traditionally, the hallmark of an APS application has been the ability to simultaneously optimize material resources, production capacity and product demand, while incorporating business rules and constraints into the planning process.

Today, the definition of APS has been extended to optimize distribution and transportation resources, as well as the resources within the four walls of a production facility. To best explain APS as a technology and its relevance to Supply Chain Management (SCM), it may help to look at how planning solutions have evolved to enable business-to-business linkages.

Today, you can’t pick up a trade or technology magazine without reading about the supply chain strategies of corporations ranging from small suppliers to global consumer product firms. CEOs are betting their collective "bottom line" on SCM principles with the hope of differentiating themselves in a market that increasingly distills everything into commodity.

Supply chains have always existed between suppliers and consumers. Likewise, supply chain philosophies have been at work for decades in American companies in the form of Just in Time (JIT) and Quick Response. Since the early 1980s, forward-thinking mass merchants, such as Wal-Mart, Kmart and Target, have been pressing suppliers for business linkages as basic as EDI on the low end and as sophisticated as Vendor Managed Inventory (VMI) relationships on the upper end.

While the ideas that make up the foundation of SCM have been around for some time, advancements in technology are driving this interest to create these new business partnerships. When it comes to SCM, there are no simple answers. However, many companies have retained consulting expertise to assess their readiness for supply chain relationships only to discover that it is not enough to have consent between trading partners – they also must have information technology to support the decisions that can come fast and furious.

These decisions must reflect an optimized response to any changing condition within the supply chain. The conditions that may alter your view of a supply chain may be related to customer demand for product, your ability to meet demand or combinations of both. Optimization, in this case, means looking at the impact of a discrete change collectively with all other changes and responding in a way that makes the best use of available production and distribution capacity.

Optimization across the entire supply chain, including internal production processes, sounds Utopian, and just a little familiar. It is reminiscent of the promise MRP II vendors made in the early 1980s to maximize plant resources with better planning tools and greater overall visibility. While MRP technology has come a long way, early design constraints placed on these mainframe-based solutions could not achieve resource optimization, as we know it today.

In the 1960s, the "father" of Material Requirements Planning (MRP), Oliver Wight, conceived the Bill of Material (BOM) explosion technique for generating time-phased component requirements for discrete finished product demand and for creating both purchase orders and manufacturing orders to meet that demand. By tying in a check for inventory, the process would subtract available inventory from the requirement so that demand for product would not be overstated.

The concept of "closed loop" MRP came years later with the first Manufacturing Resource Planning or MRP II application. This design incorporated Master Production Scheduling (MPS), MRP and Capacity Requirement Planning (CRP) as a series of demand, material and capacity checkpoints prior to launching a manufacturing order or purchase order. The "closed loop" notion was achieved by coupling the planning processes with Production Activity Control (PAC), which provided plant execution results as input to the regeneration of the plan.

Though the constructs for MRP are fairly straightforward, the mainframe technology that served as the computing platform for these early systems placed processing limitations on MRP. Limitations, such as execution speed, memory constraints and batch processing, caused early MRP application architects to move discrete order demand through the planning algorithms in a sequential and iterative manner. Below is an example of a simplified planning sequence:

• Sequence Production Demand

• Explode Customer Delivery Lead-times

• Explode Material Requirements

• Net Out Available Inventory

• Generate Manufacturing Orders (Make) or Purchase Orders (Buy)

• Explode Capacity Requirements

• Net Out Available Capacity (Finite Schedule)

• Launch Orders

Prior to manufacturing order generation, a material, capacity or master data exception could be flagged, thus sending the order back through the planning iterations. This process lends itself to batch planning on either a weekly or monthly basis. Yet, how many supply chains are so static that a monthly planning cycle could possibly represent reality?

As it turns out, the companies that have been able to consistently make good use of MRP technology have been those that enjoy long lead times, have repetitive processes, produce large lot sizes and can count on stable demand. At the risk of lumping the "World Class" MRP users into one bucket, we could hazard a guess that they are producers of commodity products that feed upper segments of a very stable supply chain – for instance, a rolled steel manufacturer that supplies the automotive sector.

Companies positioned a little closer to consumer demand have struggled to some degree with MRP results, particularly as their customers insist on shorter lead times, lumpy demand, personalized products and special services. If MRP tools could not accurately plan the internal supply chain relationships between resources in a plant, how then could such technology apply to external supply chains with any degree of accuracy? The answer is that MRP cannot optimize internal conditions – let alone respond rapidly to changes in a supply chain. Keep in mind that it is MRP II planning technology that is at the core of most Enterprise Resource Planning (ERP) software offerings today.

The pioneers of APS have had years to observe the problems with the sequential planning offered by many of the MRP-based solutions. They have also benefited from the innovative thinking of author and physicist, Eliyahu Moshe Goldratt. In 1987, Dr. Goldratt was asked to design a plant scheduling system that tripled the output of the facility. It was from this experience that Goldratt created his theory of constraints that would have planners use a five-step approach to constraint management:

• Identify the Constraint

• Exploit the Constraint – protect with buffer of material or capacity

• Subordinate all other Constraints – forward or back schedule from the point of constraint

• Elevate the Constraint – increase performance at the bottleneck relative to business goals

• Create No New Constraints

In applying the theory, early adopters learned that corporate policies sometimes create constraints that must be eliminated prior to modeling resource-based constraints. Corporate constraints, for example, could be maximum inventory levels to be carried or resource utilization being used as a performance measure. Such policies could run counter to true resource optimization.

The APS architects also learned that when properly modeled, constraints can move from one resource to another based on the product mix and volume of production at any given time. These revelations created a dilemma that MRP solutions were never designed to overcome. How can we at once model resources, identify bottleneck(s) fully constraining those resources and end up with the optimal sequence for demand that meets defined business objectives?

In the late 1980s, a breakthrough came when the first scheduling tool ran memory resident. This early APS architecture allowed the resource model to be loaded into memory along with the business rules that could be used by the planning algorithms to optimize resulting schedule. With all known demand (orders and forecasts) and all available resources (material, labor and capacity) presented to the math engine at once, requirements could be exploded and order sequences could be optimized to meet a stated business objective.

Depending on the business objective, the schedule could be optimized to reduce cost, increase resource utilization and minimize inventory, or a weighed combination of all these objectives. Memory resident execution is at the technical core of nearly every APS software product. These systems typically require a dedicated server with very large amounts of RAM to process the simultaneous math model and to present planning results with sufficient speed.

Using the premise that "a resource is a resource," APS has been successfully applied to constrained environments outside the shop floor. Basing their design on APS technology, a variety of planning tools from an equal variety of vendors are available in the market and effectively cover the following needs:

• Demand planning (forecasting)

• Distribution planning

• Transportation planning

• Supply chain logistics planning

• Manufacturing planning and scheduling

While these solutions may vary on detail features and functions, they all present the end user with a graphical view of the resource model. By allowing the planner to interact with the model by moving graphic objects rather than modifying data, the use of the tool is more intuitive and the response to a planning exception becomes less cumbersome.

Having already mentioned that ERP planning is basically MRP II, it is significant that ERP and APS solutions can coexist. Most APS solutions are not transaction-oriented systems. These systems typically do not process the business transactions that result in updated inventory statistics, booking customer orders, reporting production status or a host of other transactions that reflect activity in any given enterprise.

For many of us, the integrated functionality that defines most ERP systems is well-understood. You can view the role of ERP in an application to application relationship as basic "plumbing." ERP supplies the basic data infrastructure that enables a strong decision support tool like an APS solution.

As it turns out, these ERP systems are good stewards of the business transactions needed by the APS software. By moving data, such as inventory, customer orders and product specifications, from ERP repositories to an APS server, the planning application can react to the latest information and pass the planning results back to ERP for execution.

Is an ERP implementation a prerequisite to a successful supply chain optimization? No. If your legacy application(s) are providing the enterprise with accurate inventory (+90 percent) and a reliable demand picture (customer orders), then you have the makings for a solid APS application. The data integration is easy. The major concerns in any APS implementation are clean input data and accurate modeling – of both the inter-workings (production processes) and extra-workings (supply chain relationships) of the enterprise.

Yielding to the demand for better tools, many ERP vendors have bought or partnered with APS vendors to extend their own capability. As an example, PeopleSoft (Pleasanton, Calif.) bought Red Pepper Software for its production scheduling tools and Distinction Software for their demand planning capability. Most recently, J.D. Edwards purchased Toronto-based Numetrix to flesh out its supply chain-planning offering. Oracle Corporation (Redwood, Calif.) has had a longstanding partnership with i2 Technologies by integrating many elements of i2’s Rhythm Planning Suite.

While many more examples of ERP/APS partnerships exist, SAP AG (Waldorf, Germany) is growing its own advanced planning solution – Advance Planning and Optimization. SAP promises the same rich planning functionality found in other APS offerings with tight integration to the material management, sales and distribution, and manufacturing execution modules of its R/3 software. As of this writing, factory scheduling is in beta release with two key SAP customers.

Today, there are great examples of APS implementations all around the globe and in nearly every industry segment. Both large and small companies have built, over time, powerful applications that have enabled and continue to manage their key partnerships.

For example, with the vision of becoming marketing-oriented rather than manufacturing-oriented, a major U.S. snack food company has been using APS tools to move to a "fast pull" replenishment system. This concept allows product to be replenished based on demand at any point in the distribution network. With resources optimized by a factory scheduling solution, the thought and energy that was needed to plan the manufacturing process is now channeled into innovative methods for marketing and replenishing across a vast, complex supply chain.

The scheduling tool alone has produced tremendous results – 50 percent improvement in internal capacity utilization. This efficient use of resources and ability to respond to promotion-driven demand has freed the company to model supply chain replenishment at their lowest level of product distribution, the delivery truck.

If your business is moving headlong toward formal supply chain relationships, take the time to assess your readiness. Clearly, you have options for deploying APS technology and the supporting business transaction infrastructure. Thoughtful consideration of what is to be accomplished and what role information technology will play should proceed any supply chain project.

Examine your existing planning process. Better tools will shorten your planning cycle. Launch an effort to "get the fat out" of your planning cycle even without new tools. This exercise will point out the potential impact of better planning. You will discover how change will affect your planners and how well your enterprise can respond to change at the execution layer.

Once internal issues are understood, it still boils down to the willingness of the trading partners to use information to manage the relationship. Good partners work together. Belief in a partner’s intention is just as critical as belief in your partner’s planning numbers. There are plenty of instances of retailers, for example, who have forced their suppliers into electronic relationships that resulted in tactical responses that only benefited the retailer.

Keep in mind that even the best planning technology can be poorly applied and not every link in a supply chain requires automation. Attack your pain first. If inventory accuracy is in question, start with better inventory control. If you can’t commit to a customer due date based on an inaccurate production schedule, explore a production optimization tool and start there.

Elements of successful APS supply chain initiatives are:

• Assess your readiness up front (process and technology).

• Fix your internal processes (planning and execution).

• Involve only one or two partner(s) at first.

• Retain expert supply chain advice.

• Take "baby steps" in your implementation.

You have a choice. You can either seize supply chain opportunities through APS optimization technology or, simply, be seized.

About the Author: Rich Cauthen is Practice Manager, Supply Chain Solutions, for Osprey Systems Inc. in Charlotte, N.C.