Five Key Factors to Creating a Demand-Driven Supply Chain
The issues organizations face
Over the past four decades, manufacturing, distribution and some service companies have invested significant management time, consulting dollars and technology expense into efforts to properly balance supply commitments and realized demand. At the same time, they have been working hard to optimize trade-offs between working capital (inventory), operating expense and customer service. The results have been spotty at best. Measurable, lasting success has proved broadly, and somewhat surprisingly, elusive.
If this was a simple task, good organizations would have mastered it long ago. As it is, most have their efforts rewarded with frustration and change inertia. Many well-intentioned S&OP initiatives are chartered, staffed and supported with investment, yet they quickly plateau and wane without measurable payoff.
Symptoms of failure reach the executive suite in predictable forms:
- Demand/supply imbalances: Too much inventory creates requirements for working capital that cause financial disruption. Too little, or the wrong inventory, out of time/place sync with customer demands, damages customer trust and financial results in the form of lost revenue
- Supply chain sub-optimization: When S&OP decisions are made in functional isolation, the predictable result is sub-optimization of the company's end-to-end supply chain. Either manufacturing costs get optimized while logistics and inventory carrying costs skyrocket, or logistics decisions are optimized at the cost of efficient plant operations
- Data-deficient supply chain operations: Too often bottom-line financial results point a finger at problems in the supply chain but organizations lack the data insights to unravel the problem. Data deficiencies, and the ensuing blame game, become an accepted way of doing business
- The lack of integrated, anticipatory business plan: A failure or inability to plan creates an unpredictable business model, which creates uncertain business outcomes. An inability to predict and forecast forward-looking business performance creates a tense shareholder relationship with investors looking for predictability and control
- Functional silos, cost-savings fatigue: When everyone recognizes a cross-functional problem but no one is capable of leading a cross-functional solution, organizational distress is inevitable. This dysfunction, combined with cost-savings fatigue, disables the engines of change. This quickly escalates to become a strategic, C-level problem
S&OP success stories across decades of effort are few and far between and often tragically short-lived. Yet, despite a long, well-documented history of failures, S&OP consistently shows up as a top-three priority for supply chain executives across surveys.
Five critical success factors have proven elusive:
- Demand signal capable of driving effective, efficient anticipatory decisions. As one executive explains it, when you're driving slowly on a straight road, you can rely solely on the rear-view mirror for guidance. However, if you're driving a sports car at high speed on a windy road, the rear-view mirror alone is no longer sufficient. Similarly, a demand signal sufficiently accurate to enable correct anticipatory decisions is mission critical to efficient S&OP. Whether that signal comes in the form of a demand forecast, point-of-sale (POS) data, or some other data analytics source, it has to be accurate, timely (allowing time to react operationally) and sustainable
- Collaboration, integration, synchronization across supply chain functions: Effective S&OP is entirely reliant upon removing the imbalances engendered by borders of any kind in the supply chain. Paradoxically, it's easier to remedy silos and inefficiencies across companies than to break down internal functional barriers. Collaboration, integration and synchronization is a winning formula for effective S&OP
- Creation of a perpetual learning function: A learning system is an under-appreciated business capability that underwrites all successful S&OP efforts. The philosopher and essayist, George Santayana, first coined the phrase, “Those who don't remember the past are doomed to repeat it.“ So it is with company's who fail at the task of effective S&OP. They experience a kind of supply chain 'Groundhog Day', reliving the same failures month after month, quarter after quarter, year after year in a, seemingly inescapable, cycle. Effective S&OP capability demands the ability to incisively and insightfully dissect current period operations and correct failures in the sales and operation plan for the coming period
- Advanced data analytics capable of multivariable, multi-equation optimization: A common criticism of S&OP as a valuable business capability is that it requires the organization to believe in a calculated number. Let's face it, the task of enticing a cross-functional group of leaders to believe in a number approaches impossible if that number isn't correct to begin with. It's often been the case that, while the direction was correct, the information and analytical capabilities were not quite up to the task of getting it right. This should all change in the era of big data and advanced data analytics capabilities. These technologies are capable of delivering the right answers, even in a highly complex, multivariable, multi-equation environment
- Unbending dedication to Total Value Optimization™ (TVO): More than any other root cause of failure in historical S&OP solutions, a lack of dedication to optimizing the whole instead of its component parts stands out. The backbone of successful S&OP is an immovable dedication to dynamically anticipating and meeting demand through the synchronization of the buy-make-move-fulfill digital supply chain to deliver the greatest value to customers and investors at the lowest cost to profitably serve its customers. What we call TVO™.
Effective S&OP in action
We were asked to help a major manufacturing company that had little sales and marketing ownership in its S&OP process. This resulted in high plan operating costs and low inventory turns. We worked with them to design and implement a new S&OP process that aligned clear functional responsibility and goals for inventory reduction with new common KPIs. The new approach improved responsiveness to real demand and reduced legacy inventory by 20% in three months.