Introduction: The Enterprise Planning Challenge
Enterprise Planning has come to the forefront of the corporate agenda. Improving the accuracy and timeliness of internal planning increases
revenue predictability and operating margins—key to survival in a softening economy—and is often a prerequisite to participation in inter-enterprise collaborative planning networks. Furthermore, a growing number of businesses recognize that not all resources can be managed on a
“just-in-time” basis—downstream Enterprise Resource Planning (ERP), Supply Chain Management (SCM) and other operational system efficiencies still depend on the quality of demand signals fed to them.
Even those companies that have invested heavily in supply chain management, demand planning, and business intelligence software continue to struggle with accuracy and speed. The results are missed revenue targets, excessive and inadequate inventory levels and reduced customer satisfaction, as illustrated by a recent corporate Planning controversy. Despite a $40 million investment in supply chain software, a major shoe manufacturing was faced with bloated inventories in some product lines and shortages in others.
The company partially attributed its inventory problems to inaccurate demand forecasts generated by its new demand planning application. Quarterly earnings came in at 33% below initial estimates. And why?
Effective planning requires more than merely selecting the optimal set of supply and demand planning approaches. It also involves an integrated process that leverages enterprise-wide data, qualitative knowledge, identification of strategic constraints, and performance feedback –at its essence, effective planning requires a systems approach. This is the first nexus between Planning and the Theory of Constraints (TOC).
The second nexus between Planning and TOC is in its application. Fundamentally, TOC-based manufacturing processes are based on the pull approach (drum-buffer-rope) and constraints-based thinking
(see Figure 1 below). In TOC, the identification of constraints is fundamental. To identify constraints however, requires effective and timely management of demand signals and supply requirements.
In the broadest sense, a manufacturing organization that follows TOC principles should also consider alternative ways to manage demand to better match existing constraints. This practice, known as demand management and exemplified by the Sales and Operations Planning Process (S&OP), is the logical evolution of enterprise-wide consensus forecasting and supply planning processes.
Figure 1: Basic principles of constraints-based thinking
Pain Points: Data and Employee Knowledge Accessibility,
Process Management
Given its inherent complexity, cross-departmental demand management is a painstaking activity, grounded in both science and art. The data required exist in disconnected operational systems while vital qualitative knowledge is isolated within departmental silos. As such, the greatest challenges to enterprise planning lie in the ability to efficiently (1) integrate disparate data
and qualitative departmental knowledge and (2) manage the supply-demand balancing process. Making it work is often a Herculean, resource-intensive task that becomes increasingly complicated and time consuming as stakeholders are integrated into the process. Any single information
bottleneck can substantially slow down the entire process.
Sales and Operations Planning supports the traditional planning process,
but differs in two ways. First, it reviews planning activities at a higher level,
on a monthly and yearly basis, rather than the tactical daily or weekly planning in the traditional process. This is critical as it allows a company to proactively identify and manage upcoming issues like overstock situations, fixed capacity constraints, regional velocity of demand and financial reserve accruals. Secondly, senior management is heavily involved in S&OP with the goal
of driving consensus on a single operating plan across business functions.
The following illustration provides a high level view of the integrated planning process.
Enterprise Data and Functional Silos
Figure 2: Planners are typically unable to easily access and integrate the data they need as it resides in disconnected systems—Customer Resource Management (CRM), Supply Chain Management (SCM), Enterprise Resource Planning (ERP), legacy systems and excel spreadsheets.
Planning data inputs
CRM |
SCM |
ERP |
Legacy systems |
Spreadsheets(exogenous data)
|
Sales pipeline,
with confidence
levels, pricing
data, customer
and order
prioritization |
Potential
demand,
supply,
constraints,
future orders,
long-term
capacity
options |
Historic sales, pricing, currency exchange, new products, short-term supply availability, inventory |
Past forecasts, underlying assumptions, accuracy |
Econometric data, leading indicators, pricing information, marketing programs, POS, trading partner data, qualitative analyses |
Figure 3: Information relevant to enterprise planning exists in different information systems across the enterprise.
They likewise often do not have visibility into the exogenous factors that drive their business, the invaluable qualitative knowledge that exists throughout
the organization, or the validity of past forecasts.
Departmental qualitative inputs
Marketing |
Sales |
Operations,
Logistics
|
Finance |
Executives |
| New products, product changes, promotions, channel placement, pricing, market research |
Customer priorities, changes in customer behavior, competitor intelligence and pricing |
Supply constraints, cost and part trade-offs |
Revenue and profit targets, budget effects,
macroeconomic insights |
Strategic plans, new initiatives |
Figure 4: Different qualitative and subjective information exists across
different departments.
Integrating business drivers into a statistical forecast, adjusting the forecast based on employee qualitative knowledge and historical accuracy, and communicating the results throughout the organization are key to improved forecasts, planning and decision-making.
Marketing |
Sales |
Operations,
Logistics
|
Finance |
Executives |
Existing and
new product planning,
promotion
planning,
channel
placement,
Pricing |
Sales
quotas, targets, fulfillment options, available-to-promise options |
Production,
plant,
equipment, transportation, warehousing, assembly, workforce/
staffing, and customer
service
planning |
Revenue
and earnings planning, budgeting, capital requirements |
Investor relations, strategic and business planning |
Figure 4: An accurate enterprise forecast can benefit each part of the organization.
To get the process “right”, analysts are often required to manually manage
and facilitate the demand planning process across departments, business units and geographic regions while manually “crunching” the data and integrating qualitative forecast adjustments. Analysts manually shuffle excel spreadsheets; track down process snafus; translate forecasts into units relevant to user-specific roles and functions ($/units by Business Unit, Region, Customer, Item, etc.); identify, analyze and reconcile gaps at multiple levels of inter- and cross-departmental forecasts; and generate and disseminate the forecast, plan, and performance results.
Resource-Intensive System
Figure 5: Current enterprise planning processes are extremely resource intensive and are not driven in a consistent, reliable way.
Frustrated by the complexity and the resources required to reap the benefits
of enterprise planning, functional managers often instead rely on their intuition or unilaterally modify forecasts provided to them based on their experience, without communicating these adjustments to the rest of the organization. Subsequent planning and decision-making activities suffer from lack of
shared insight. The effectiveness of operational systems is compromised.
Resources are misallocated. Corporate objectives—including revenue, profitability, and customer service and performance targets—are often not achieved. Fortunately, the technologies to overcome the obstacles of
cross-departmental Planning are now available.
Footnotes:
#1. 75% of companies view improved Planning accuracy as critical to their organization. (Industry Directions, Inc. (2003).
#2. “Only 25 percent of companies incorporate predictive metrics in their plans.
Top performers, by contrast, strike a balance between the financial and
operational perspectives, both leading and lagging.”
Hackett Benchmarking & Research (June 2001).
About the Author:
Glen Margolis is Founder & Executive Vice President of Services
at Steelwedge Software. Glen is a veteran of multiple startups and founded
a successful contract manufacturing organization. He was a senior supply
chain strategy consultant with Mercer Management Consulting and Ernst &
Young. Glen holds a Bachelor's in Engineering from the Webb Institute
and a Masters in Finance from Harvard University.
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