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Advancing the cause of supply chain management and sales and operations planning through advanced analytics.

Organizations have talked about integrated business processes for decades, but most of us still operate in silos. The result is inefficient supply chains and disappointing results from S&OP. To realize the promise of SCM and S&OP, organizations need to apply new analytic tools and a network view of the supply chain.

Supply Chain Management. The words are a freely exchanged coin of the realm. The promise is considerable: an overarching discipline that incorporates all of operations, finance, customers, suppliers, and even research and development as well as critical aspects of sales and marketing into a single scope that ultimately focuses on maximizing the financial performance of the firm. Yet after over 50 years of evolutionary development, reality has fallen well short of expectations: Cross-functional integration is impeded by corporate organizational structures, culture, and inappropriate performance metrics.

Certain processes and tools, most notably sales and operations planning (S&OP), have been developed to address such shortcomings. Yet these have often failed to live up to their promise as well, often due to inadequate decision support technology. This results in substantial expenditures of time and money with little of substance to show for the effort. So, are SCM and S&OP misguided and overrated? Or, is it a matter of not having the right analytics tools and implementation processes?

Those are questions we will explore in depth over the following pages. Before that, let's be clear at the outset what this article is not about. First, it is not a primer on either SCM or S&OP. That territory has already been mapped by others. Rather, we assume that the reader has a working knowledge of both subjects. It is also not a comprehensive presentation of analytics--advanced or otherwise.

We do so to set the stage for how the causes of SCM and S&OP have been hampered by a silo management mentality and how they can progress by means of advanced analytics. We then extend S&OP to a level beyond even Integrated Business Planning (IBP) by using an extension of the same analytics.

Sales & Operations Planning

Let's begin by setting a baseline for S&OP. Definitions abound; here is a representative one published in Supply Chain Digest from Wallace and Stahl:

A set of decision-making processes to balance demand and supply, to integrate financial and operational planning, and to link high level strategic plans with day-to-day operations.

From such concepts has grown an immense literature about the S&OP process, typically presented as a series of steps that might include:

* Data gathering.

* Demand planning that assesses historical accuracy and generates collaborative (cross-functional and customer input) forecasts.

* Supply planning, to assess historical accuracy, determine capabilities (procurement, manufacturing, logistics), and develop feasible plans to synchronize supply and demand.

* Working group meetings that identify conflicts and propose resolutions, assess those plans against corporate strategy and financial goals, and set the agenda for the executive meeting.

* Executive meetings where recommendations are reviewed, conflicts are resolved, plans are assessed against strategies and goals, and a plan is approved and issued.

Some authorities argue for seven, nine, or even 10 steps in the process. Our advice: Pick a representative set that is relevant to your organization and focus on implementation.

The above and related literature demonstrates that S&OP is fundamentally a cross-functional process that seeks to balance--or synchronize--supply and demand. If only it were as simple to implement as it is to describe.

Evolution of Supply Chain Management

Before we move forward, it's helpful to take a quick trip down memory lane to examine the evolution of supply chain management, with particular emphasis on aspects of cross-functional integration critical to successful implementation of S&OP. A convenient starting point is the 1960s, a decade that saw the first real studies dedicated to the study of physical distribution management, as well as the founding of the National Council of Physical Distribution Management (NCPDM), a precursor to the current Council of Supply Chain Management Professionals (CSCMP).

The focus was squarely on the distribution of finished goods or the flow of product from the end of the production line to the customer. Procurement and manufacturing were separate areas of expertise, more or less divorced from each other and certainly from distribution.

Worse yet, finished goods distribution was really a disparate set of responsibilities spread throughout the organization with no single manager in charge. The result was separate silos for procurement and manufacturing, and well, a rather disorganized mess.

Around this time a few lonely voices suggested a better way. One of the most prominent was Dr. Bernard J. (Bud) LaLonde, now a Professor Emeritus at The Ohio State University, who prepared the diagram shown in Exhibit 1. Procurement and manufacturing were shown together as materials management and the aforementioned disparate functions were collectively labeled physical distribution management. But the remarkably prescient conceptual breakthrough was the bottom line: The whole thing, indeed all of operations, was collectively called "business logistics." The implication was clear: It should all be managed within a single scope of responsibility.

Predictably, community resistance was fierce. No vice presidents worth their well-honed turf protection skills would willingly cede their domains to an upstart overarching discipline. Any logistician who suggested otherwise would be unceremoniously sent to their silo penalty box, such as it was. And truth be told, few logisticians shared this integrated view, anyway. The 1970s saw some genuine improvement. The disparate functions within physical distribution were gradually organized under a single manager--only rarely a vice president. However, as shown in Exhibit 2, silo management was still firmly entrenched: We now had three silos instead of two. The fundamental driver was considered truly breakthrough at the time: The total cost concept stated that what mattered was the sum of all physical distribution costs, not the cost of any one activity. One made improvements by identifying cost tradeoffs across functions but within the silo. This basic application of a bottom line perspective may seem quaint in retrospect but it was a major focus of professionals in the 1970s and is still valid today.

By the 1980s there was renewed interest, at least in academic circles, in the larger notion of cross-functional integration. NCPDM was renamed the Council of Logistics Management (CLM) in 1985 and their corresponding definition of logistics encompassed all commodity and related information flows. Similarly, faculty members of Michigan State University presented the results of an important study that identified the attributes of leading edge firms in logistics. One of them consisted of subsuming the silos shown in Exhibit 3 under a single line-level vice president. The researchers called this "integrated logistics management," an idea consistent with LaLonde's notion of business logistics developed two decades earlier.

Remarkably, it has been the author's experience over the past 40 years that silo management still reigns supreme.

To wit:

* At numerous professional conference presentations, informal show-of-hand surveys reveal that only a tiny fraction of a given audience hails from firms where a single line-level executive has responsibility for procurement, manufacturing, and finished goods distribution.

* What's more, in our experience, many industry leaders strictly limit

the scope of the analysis to finished goods distribution, despite our strenuous objections. This even in light of world-wide supply chains, where matters such as the location, mission, costs, and capacity limits of procurement and manufacturing are critical to overall supply chain design and operation, not to mention related issues such as duties, taxes, customs and brokerage fees, intellectual property theft, vulnerability, and so on. That is, the conventional silos are inextricably intertwined. Nevertheless, it has not yet migrated into most organization charts, operating procedures, or analytic scopes.

* And we have not yet discussed the stretch goal beyond operations: the integration of operations with sales and marketing. Is that even possible? More on that later.

But wait, you protest. What about supply chain management? Doesn't it imply a single scope of responsibility across the entire supply chain? Well, yes, at least in theory. The term first appeared in the early 1980s and finally gained traction in the mid-1990s and beyond. Yet the silos from the 1970s largely persist. The organizational structure, metrics, and analytical tools impede progress. We talk much more than we walk.

One of the more sophisticated notions of SCM has been developed by members of The Global Supply Chain Forum sponsored by The Ohio State University:

... the integration of key business processes from end user through original suppliers that provides products, services, and information that add value for customers and other stakeholders.

They go on to develop in detail eight such processes:

* customer relationship management;

* customer service management;

* demand management;

* order fulfillment;

* manufacturing flow management;

* supplier relationship management;

* product development and commercialization; and

* returns management.

And they do mean cross-functional. In this view, representatives from procurement, manufacturing, logistics, R&D, sales and marketing, and finance form actual teams for each process that set strategic objectives and operational responsibilities. In short, they establish the imperative and the procedures for collaboration across functions, and they tie the results to corporate financial goals. And, by means of customer relationship management and supplier relationship management, they include members of the supply chain that are outside traditional organizational boundaries. So, here is our bottom line with respect to SCM evolution:

* SCM prescribes cross-functional integration; however, theory has far outstripped practice.

* We do not lack for the bandwagon effect. No self-respecting professional, whether practitioner, academic, or consultant, would fail to utter the words "supply chain" when describing their role. In reality, however, we practice silo management.

* There are underlying organizational impediments to the successful implementation of any inherently cross-functional process such as S&OP. In particular, rare is the presence of an executive with the requisite line authority to mandate compliance across all of operations.

Regrettably, due to space limitations we must mention only in passing an additional major impediment and a critical topic in its own right: the metrics chosen to establish goals and measure supply chain performance.

Seen in this light, the unsatisfactory results of many S&OP efforts are more understandable. Yet we need S&OP, or its equivalent, to bridge these divides. Can it be implemented to meet the challenge?

Strategic Supply Chain (Network) Design Advanced Analytics Tool

Most readers probably have at least an informal understanding of an optimization-based strategic supply chain (network) design tool. But because numerous misconceptions persist, we provide a summary of the salient details.

Exhibit 4, on page 16, shows a simplified schematic of an international supply chain (the ships represent ports). Obviously, this is but one example of a large number of variations that may, for example, include other types of locations (pool points, cross docks, rail heads, and so on) and other transportation links (for example, plant direct to customer). To avoid clutter we also do not show alternative customer channels (such as omni-channel) and various types of commodities. The latter may include raw materials, intermediate products, and finished products.

An important extension, one critical to S&OP, is to build a multi-period network model. In this instance, one partitions customer demand into time "buckets" such as months. Other volume-related inputs such as capacities are similarly defined. The model has simultaneous visibility across the entire planning horizon. In particular, inventory can be passed from one period to another, thereby enabling seasonal pre-build analyses.

Using Exhibit 4 as a guide, we summarize the inputs, both mandatory and optional:

Network Description

* commodities

* raw materials

* work intermediate products (WIP)

* finished products (typically aggregated from SKU level)

* locations

--raw material suppliers


* drill-down to lines/processes


* drill-down to lines/processes

--customers (typically aggregated from ship-to level)

* Other

--customer channels

--time periods

* Customer Demands

* table by customer/channel/finished product/ time period

* Transportation Costs

* inbound (supplier to plant)

* transfer (between facilities)

* outbound (to customer)

* Facility Data (mostly optional)

* mission data (eligibility of commodities at a given location)

* procurement costs, capacities, and violation penalties

* manufacturing costs, capacities, and violation penalties

* DC location costs, capacities, and violation penalties

* bills of material

* inventory targets and holding costs

* stock open/close options

* Other (optional)

* duties, taxes, currency conversions

* selling prices (needed for profit max studies)

* customer service limits

* data scaling options

* energy usage and carbon emission factors/ constraints

Following are several pertinent observations:

* Notice that the list is consistent with the operating characteristics of a complete manufacturing supply chain. No aspect of operations has been omitted.

* While virtually all of the facility data is technically optional, their omission would cripple the application of this technology to S&OP. This is the time to go deep with respect to these inputs. In particular, one must pay attention to capacities such as procurement, manufacturing, throughput, and storage.

* The more accurate the operating costs the better. In particular, while activity-based costing values are not essential, they serve as a welcome improvement to the meaningless financial averages too often used as shortcuts.

The model is formulated as a mathematical optimization problem, more specifically one that requires a mixed integer linear programming algorithm to solve.

The challenge is to find the set of facilities and transportation links and associated product flows that either minimizes total costs or maximizes total profit, subject to the following restrictions and constraints:

* procurement contractual limits;

* manufacturing capacity limits;

* DC throughput limits;

* storage limits;

* inventory targets;

* customer service limits;

* other transportation link restrictions;

* energy consumption limits; and

* carbon emission limits.

S&OP, SCM, and Advanced Analytics

Despite theory, expert consultants, and best intentions, let's see how S&OP too often evolves in practice:

* Sales and marketing come to the meeting armed with spreadsheets containing their latest forecast.

* Manufacturing sits down with the latest capacity numbers, also in (you guessed it) spreadsheets.

* Manufacturing professes to be appalled by the implications of the forecast and once again concludes that sales and marketing haven't a clue about the real world of operations.

* Marketing responds that their aim is to maximize corporate revenue by satisfying customer requirements.

* Both parties argue, compromise, adjust respective spreadsheet numbers, and with sighs of relief all around, agree on a plan to present to senior management. No one knows how much money has been left on the table and there is no way to find out--the problem seems overwhelmingly complex. Finding something that at least works is deemed an acceptable outcome.

* No one leaves satisfied, all believe that there must be a better way, and resentment toward S&OP builds.

Little wonder that in too many instances, the S&OP process is consigned to the trash heap of promising ideas that ultimately fell short of expectations.

Let's unpack the typical process just a bit to understand some of the reasons why it fails:

* Sales and marketing typically develop the forecast. Wrong. SCM principles tell us that every process must be fully cross-functional. All of the principal functions must participate in developing this critical input, including sales and marketing, procurement, manufacturing, logistics, finance, important customers, and so on.

* The synchronization scope is often limited to manufacturing. Wrong again. SCM principles tell us that it should span the entire supply chain.

* The methodology used to establish the synchronization is almost always remarkably ill-suited to the challenge, typically what has been accurately dubbed by an experienced participant as "warring spreadsheets."

These are important limitations. Perhaps the most disappointing is the utter lack of appropriate analytics to address synchronization.

Network Design: There Must Be a Better Way

So what can be done to improve the shortcoming of the analytics? Consider the strategic supply chain design tool. Once again you protest: Isn't that the stuff used for facility location studies? In one sense, yes. Supply chain design tools were originally developed to address facility location questions; to this day, that is a very common application. However, their contemporary scope is much more extensive, as illustrated by the following list:

* the number and location of raw material suppliers, plants/vendors/co-packers, production lines/processes, and DCs, pools, cross-docks, and ports;

* transportation links and flows, including inbound from suppliers to plants, transfers between facilities, and outbound to DCs and to customers;

* facility ownership issues, including owned, leased, public, and 3PL facilities, and outsourcing;

* facility mission issues, such as commodities procured, manufactured, distributed per location, and costs and capacities; and

* business decision/policy issues, such as strategic sourcing, customer profitability (cost-to-serve), S&OP, supply chain/marketing integration, and energy/ carbon footprint/sustainability.

Notice the mix of issues traditionally considered as strategic with those regarded as tactical, the latter including S&OP, master capacity planning, and seasonal demand/supply. So how do we persuade a strategic network design tool to support the tactical world of S&OP? Consider the following approach:

* Build a truly comprehensive, multi-period model of the supply chain, from raw material acquisition to final customer demand. Specify a suitable period.

* Freeze all customer assignments to pre-determined customer facing locations.

* Use forecasted demands for the relevant planning horizon (typically 12 to 18 months).

* Lock down the facility locations but not the facility volumes or inter-facility transportation flows. Note: At least some open/close decisions at the production line level are typically left to the discretion of the model.

* Run the model.

What, then, is the moral of story? One need not do a "wide-open," full-scale network optimization whenever using such a tool. Rather, one can pre-specify components of the network. In this instance, one could pre-specify customer assignments and the open/close status of facilities and still leverage the tool's considerable power, most especially its ability to adjudicate limited capacities. This is much more realistic in the short term; one does not redesign a supply chain on a monthly basis. In fact, numerous authorities recommend a redesign analysis at least annually. This contrasts favorably with the practice of many firms to re-examine this issue every three to five years, or longer.

So what do you get for your trouble? For starters, all of the following, reported by period and commodity:

* raw material requirements by supplier;

* production volumes by location and line/process;

* storage requirements by location;

* throughput volumes by location;

* inventory carryover;

* transportation flows by lane;

* total costs;

* capacity utilization analysis (including violations); and

* energy and carbon audits.

Notice that this is precisely what we want from the supply/demand synchronization step in the S&OP process and, in most cases, is far more extensive than what most S&OP processes can deliver. Moreover, it uses truly advanced analytics (optimization), which is the only type of analytics, advanced or otherwise, capable of properly addressing two issues inherent to S&OP: the necessity to allocate limited raw material, manufacturing, and storage resources (capacity limits); and open/ close decisions by production line and shift.

We repeat: These mathematically and managerially complex issues cannot be properly addressed by heuristics, expert systems, simulation or, worst of all, spreadsheets. The real irony here is that the above is a classic example of a problem that has been extensively studied for decades in the operations research community and is very well understood. So, what have we typically done with this body of knowledge? We have thrown it out in favor of simplistic spreadsheet wars that are virtually guaranteed to produce substandard results.

A critical benefit: At least with respect to cost minimization, the problem of leaving money on the table disappears. Optimization eliminates the guesswork, the compromises, and the myopic search for something that works. It deals with the apparently daunting complexities head-on, without restriction.

The next time someone approaches you with a proposed S&OP process, drill down hard on the details. Be especially wary of the supply-demand synchronization step. Do not accept the response: "We use analytics." It is a catchall buzzword that can mean anything from basic descriptive statistics through predictive approaches to truly advanced prescriptive tools and a whole host of options in between. And spreadsheets are unquestionably the most overused analytics tool in existence ( when all you have is a hammer.....").

One final methodological note: There is nothing to prevent one from developing a special purpose, optimization-based package to address a given S&OP problem. And in certain specialized instances with many idiosyncratic details, that is the correct approach. But custom applications are time consuming and expensive to develop, certify, maintain, and support. It is far better to use readily available tools where possible.

Major Extension: Integrating Supply Chain and Sales & Marketing

Let's go back to the evolution of SCM for a moment. Most definitions, and virtually all practitioners, focus on traditional operations, however partitioned they are into silos. The closest one comes to integrating sales and marketing with operations lies with approaches such as those advocated by the Supply Chain Forum discussed above, wherein customer relationship management, customer service management, and demand management are explicitly recognized by other authorities as cross-functional business processes.

So, too, for advanced analytical tools that focus on supply chain strategy and tactics such as those presented above. Beyond the presentation of demand, there is no explicit consideration of sales and marketing activities in traditional network design models.

S&OP, on the other hand, is all about synchronizing supply and demand. The process forces sales and marketing teams to sit down with operations and adjudicate differences. It begins with a demand forecast, preferably generated by a cross-functional team. If we examine that forecast closely, we see that it typically contains the estimated impact ("demand lift") of various scheduled marketing campaigns or initiatives. The challenge is to respond to forecasted demand levels, which are taken as a given.

But this process begs several important questions. Even if the initiatives are successful, should they be implemented at all? Are they worth the cost? And can we answer such questions while simultaneously addressing the synchronization issues?

We can address all of the above questions analytically. But to do so we must change our focus from the traditional metric of cost minimization to the uncomfortable notion of profit maximization. Why uncomfortable? Ask yourself the following: Beyond a subset of the executive suite (CEO, CFO), whose compensation is based on profit maximization? The honest answer is no one. Consider that classic performance metrics tied to sales force compensation, the success of marketing initiatives, manufacturing utilization, and procurement stress volume, not profit and maximization.

Are there additional metrics specific to certain functions? Of course there are. But the entire organization readily lines up behind volume and cost. So how can we approach this problem analytically? The answer is to describe to the model each proposed marketing initiative.

* Budget: fixed and variable costs.

* Activity limits for the given budget (e.g. number of new hires, advertisements purchased, etc.). These are effectively "capacity" limits.

* Anticipated demand lift.

* Add selling prices by customer/channel/product/ time period to measure revenue as well as cost.

* Instruct the model to maximize profit rather than minimize cost.

* Allow the model to choose from available marketing initiatives. At the outset, the demand forecast does not include their anticipated lift.

In turn, the model will accept initiatives that are profitable and feasible. It will reject initiatives where the selling price for a given order exceeds the cost to serve, or where there is insufficient capacity in the network to meet the requisite volume. In short, the algorithm finds the maximally profitable quantity that can actually be produced. The bottom line is a profit maximized corporate strategy to guide the CEO and CFO.

Realizing the Promise of S&OP

For many decades we have recognized that the essence of supply chain management is cross-functional cooperation, if not complete integration. Unfortunately, the evolution of the organization structures to support that concept essentially stalled in the 1970s. What remains is what always existed: functional silos without a line-level executive structure to exploit the promise of SCM. This organizational stumbling block shows no signs of going away. Nevertheless, firms have recognized the need for cross-functional cooperation and have adopted processes and tools to facilitate it--most notably S&OP. Unfortunately, the associated analytical tools are typically underpowered for the task, resulting in anger, frustration, and a lack of support.

It is possible to rescue the promise of SCM and S&OP, but the process can be long and arduous. Ideally it involves organizational restructuring, the formal adoption of cross-functional processes, and a concurrent adoption of new performance metrics. Regardless, powerful tools are needed to address the complexity inherent in cross-functional integration or supply-demand synchronization. S&OP is indeed a multi-step process that can facilitate that goal. In turn, it must be supported with suitable analytics, lest the promise go unrealized.

Jeff Karrenbauer, Ph.D. is President of Insight, Inc. He can be reached at For more information visit
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Author:Karrenbauer, Jeff
Publication:Supply Chain Management Review
Date:May 1, 2015
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