Opportunity Assessment

There are times when organizations see that the overall performance results do not support their business goals, but cannot pinpoint the real underlying issues or root cause. Our Opportunity Assessment Service utilizes Strategic Value Assessment Framework (SVA)* that leverages a set of diagnostics which is geared towards benchmarking our client's practices and metrics, then identifying misalignments to their root causes and what impacts they have on their business. Our holistic approach will scope out opportunities and present recommendations based on the overall Business Goals and Supply Chain strategies. These discoveries pave the way for a business case and a meaningful plan of action and recommendations. Jaguar-APS professionals can also assist our clients in developing a clear business case.

This service is available as a stand-alone or as part of the Business Transformation Services.

About Strategic Value Assessment (SVA) Framework

Implementing a structured demand forecasting process and demand planning (S&OP / IBP) process requires significant process redesign, not to mention the challenges and complexities from business, architectural, cultural, and political perspectives.

Understanding of how the business strategy ties in day-to-day tactical activities of process stakeholders and how they understand their role in achieving this strategy proved in our experience to be an often overlooked aspect of any typical business assessment / analysis.

The purpose of SVA is to review a company’s current demand planning (S&OP / IBP) and demand forecasting processes and integration with existing enabling systems to recommend process improvement opportunities. All of the above validated against company strategy and cultural background.

The main deliverable includes a list of preliminary recommendations and a technology proposal that outlines recommended improvements and supporting solution technology (if applicable). The final result is a detailed business case and recommended road map that will lead to an improved demand planning / demand forecasting process design supported by existing (or minimally increased) resources and enabling demand forecasting technology and data warehousing configuration.

The SVA includes “readiness assessment” that covers four primary functional areas within a company’s demand forecasting and demand planning processes as they relate to the improvement of the overall demand planning and demand forecasting processes. This readiness assessment is then examined against the company’s overall strategy.

1. Process integration

    Measure the overall degree of interdepartmental cooperation and alignment of the demand and supply process, which normally includes integration with the company Sales and Operations Planning (S&OP/IBP) process.

2. Methods integration

    Measure the degree of statistical rigor and collaboration within the current demand forecasting process, which includes statistical forecast training and understanding of basic forecasting methodology.

3. Systems integration

    Measure the ability of the current legacy technology infrastructure to support the demand forecasting process.

4. Performance integration

    Measure the extent to which calculations of forecast accuracy are aligned with key performance indicators on an enterprise level.

5. Strategy integration

    Measure of how company vision, mission and short term strategic and financial goals are understood by individual process stakeholders and how they are linked to the individual building blocks of integrated business planning (IBP) or S&OP.

Each of these integration areas is assessed to determine appropriate “development” stage within the context of the progression shown next.

The sole purpose of these classifications is to provide sustainable recommendations regarding areas that are open to improvement and the functions that could provide the greatest return.

Strategic Value Assessment Process

Over the years, experience has confirmed that the four integration areas and their link to the business strategy collectively contribute to best-in-class demand planning and demand forecasting. However, designing the right combination of the appropriate elements from each integration area is an important factor in creating a successful demand planning and demand forecasting processes.

Companies that have low forecast error and have effectively satisfied their business objectives balance the right elements with a range of practices that span across information systems, business processes, human resources and organizational dynamics, data resources and include company strategy in execution of these processes.

Companies with a balanced structured approach incorporating sophisticated statistical methods, best demand forecasting practices, and enabling technologies are more likely to be satisfied with the overall effectiveness of their demand forecast process than those incorporating either one or none of the recommended integration areas: process, methods, systems, performance and their links to business strategy.

Several proven steps are vital to conducting a successful SVA process. The SVA process consists of the following steps:

  1. Detailed interviews with internal personnel to gain understanding of their individual objectives within the framework of company, departmental and team goals, and prioritize areas for improvement.
  2. Follow-up joint discussions with each department head and team for the purpose of understanding each department’s structure, aligning expectations, exploring solution paths, and product/service education.
  3. Development of a readiness assessment that covers the four primary functional areas (process integration, methods integration, systems integration, performance integration) within the company’s supply chain structure as they relate to improvement of the demand planning and demand forecasting processes.
  4. Validation of high-level company objectives (strategy, vision, and mission) and assessment of the ability to meet those objectives within a specified time period.
  5. Summary of major challenges toward achieving those objectives in the current corporate structure.
  6. Development of a road map that outlines a course of action for a short- and long-term process design that may include an enabling solution.
  7. Design of the guidelines for development a return-on-investment (ROI) model that can be used to support and justify a business case.

An internal champion who supports the SVA process – a C-level manager, normally the vice president of supply chain management / operations, sales, marketing, or finance or the CEO – is vital. Without a champion, it will be difficult to overcome the change management hurdles necessary to implement the process redesign. The internal SVA team should be cross-functional, made up of sales, marketing, finance, demand planning, operations, information technology (IT), and other staff who participate in the monthly (or weekly) demand forecasting and demand planning processes. A project manager who ensures that timelines and milestones are met with the utmost quality and level of detail should lead the SVA team. The resulting SVA will be a true representation of the current process, reflect true individual and team objectives, and provide a framework to create a business case and implementation plan that will be acceptable across the entire company.

Typical Key Benefits of SVA:

  • Forecast accuracy improvement by 30%+
  • Improved cash flow
  • Inventory reduction by 10%-20%
  • Less inventory and better customer service in MTS
  • ROI
  • Shorter lead time in MTO
    • Cost of project implementation - within first 12 months
  • Better capacity utilization
    • Cost of new or redesigned enabling technologies (forecasting systems, data warehousing, etc.) – within 24 months
  • Handshakes developed in the top-management team
  • Improved customer service
  • Improved accountability on large projects and new product implementation
  • Improved employee moral
  • GAP closure
  • Improved profitability
  • Simplified and shortened budgeting process
  • References: