Supply Chain Potential: Feasible and Optimal Supply Chain Planning

A Supply Chain (SC) is a system of organizations, people, technologies, activities, information and resources involved in moving materials, products and services all the way through the manufacturing process, from the original supplier of materials supplier to the end customer.

Supply Chain Management (SCM) is about planning, coordinating, execution and control of the organizational entities with their supporting resource (human, machines), process and technology in moving material, products and services through different interconnected system entities to the end customer.

Supply Chain key objective is to ensure time and place utility at the lowest possible cost: just enough at the right time and right place to satisfy customer demand with a view to strive for maximum possible potentiality.  It impacts directly the organization:

• Growth and its viability by ensuring efficient and effective supply chain aligned with marketing, sales and financial strategic plans
• Profitability by ensuring the lowest possible operating costs in delivering a balance between efficiency and effectiveness, minimizing/eliminating waste and errors. Optimum throughput will ensure financial inflows and reduce inventory levels
• Optimum inventory turns within optimum efficiency and effectives conditions: inventory turns to need to be associated to optimum inventory targets
• Optimum return on invested capital: striving for the highest possible potential within the efficient and effectiveness objectives: striving for optimum plant/equipment effectiveness: optimum return invested capital whereby long batch runs versus optimized batch runs will maximize throughput (batch size impacts return on invested capital, machine set-up due to change over reduces the return on invested capital)

Most organizations have a hard time minimizing the discrepancies between their capacity (what is possible or constraints) and the demands of their customers. These inefficiencies can have a massive negative impact on an organization. In this competitive environment, organizations cannot afford the luxury of being inefficient when it comes to their capacity planning (potentiality) — the balancing act of ensuring available capacity meets required capacity while maximizing the return on an organization’s assets, minimizing costs, and effectively managing risks.

An organization’s supply chain must be flexible enough to accommodate fluctuations in demand, while also guarding against investments in capacity or production before it is needed. As a result, most of them are under-utilizing resources or are unable to fulfil customer demand due to complexity: this implies poor Supply Chain Governance in terms of planning, coordinating and control achieving sub-optimum balance between efficiency and effectiveness (the right things the right way).

The performance of the system depends on how well the parts fit together, not how well they perform individually and the ‘whole’ system exhibits emergent properties that are not to be found in its parts.

The Supply Chain governance framework key objective is to always strive for maximum potentiality and optimum efficiency and effectiveness:

• Potentiality: This is what Supply Chain governors should be doing by developing resources and removing constraints, although still operating within the bounds of what is already known to be feasible. A bottleneck (manufacturing or handling resource) is a resource with capacity less or equal to demand while a constraint is a limiting factor to organization’s performance, an obstacle to the organization achieving its goal. These are imposed constraint such as a policy or method (way of working) that influence system output.
• Capability: This is what system should be presently doing with existing resources, under existing constraints, if there is management focus to eliminate waste, increase output resulting in improvements in productivity and efficiency.
• Actuality:  Current state of Supply Chain variables (output, Equipment effectiveness, forecast accuracy), with existing resources, under existing constraints

1. Productivity: is the ratio of actuality and capability
2. Performance: is the ratio of actuality and potentiality

Feasible and optimum planning should be based on capability while management effort should strive for maximizing potentiality (leverage capability). Key performance indicators should compare actuality to capability and actuality to potentiality (what is possible).

A bottleneck (resource) is a resource with capacity less or equal to demand while a constraint is a limiting factor to organization’s performance, an obstacle to the organization achieving its goal. A constraint can be a bottleneck, but a bottleneck is not always a constraint.

Constraints fall into four different groups:

• Constraints of foundation (where we are limited in something that is usually seen as a foundation element for success); internet selling does but provides the buyers to touch and feel.  Policy decision such as aligning product development around a specific operating system (Nokia).
• Constraints of resource such as facilities, manufacturing resources, people etc..  A constraint related to manufacturing resource relates to what generates output.
• Constraints of method (where we are limited by having to do something in a certain way). Typically, entrenched business processes based on ERP system ways of working that influence effective exploitation of resources and time.
• Constraints of time (where we are limited in the amount of time we have to do something). Management Constraint; limitation of the system due to management capacity or management attention. Management has a limited availability to deal with issues and control in their system sphere. Capacity management implies how many different issues can be handled over a period of time. A fundamental aspect to viability relates to autonomy; the ability of operational units to operate in autonomy within predefined control criteria freeing up management effort to deal with more complex and serious issues.

For effective planning it is fundamental to achieve a plan that is both feasible and optimal which will increase performance, reduce costs, avoid costly mistakes and boost confidence among organization areas such as marketing, production and finance and finally shareholders:

1.   capacity planning — this implies achieving system balance (continuous balancing act based on feedback loops) by ensuring available capacity meets required capacity (demand driven capacity requirements) while maximizing the return on an organization’s assets, minimizing costs, and effectively managing risks.
2. Flexibility – supply chain must be flexible enough to accommodate fluctuation in demand considering current investment in productive capacity.
3. Feasible capacity plans can be executed within the realities of the business. They must not reflect unrealistic objectives for which organization will never be able to execute given all their important constraints. A feasible plan must account for the constraints, trade-offs, regulations, policies, and the financial requirements of a business.

o   Constraint: a constraint is anything that limits an organization from being able to produce more of what it strives for. Some constraint examples are labour, production equipment, warehouse space, transport limitation and third-party supplier capacity limits, way of working (process).

o   Regulations: Organization such as the chemical industry, pharmaceutical and food industry are heavily regulated from a compliance perspective when it comes to their production.  Production flow are impacted by batch control, compliance and traceability: higher inventory levels to off-set validation time (quality checks)

o   Financials: what is produced (product), quantity that is produced (batch size) and quality impacts the financial situation of the organization such as cashflow perspective. If an organization fails to convert its output to income fast enough, they could find their survival being threatened. An organization may be able to physically increase production by running over-time shifts, but this may not be practical from a financial standpoint.

·         For a plan to be feasible, it must be able to meet the output given the constraints over a specified time period. A feasible plan represent reality, it must reflect organization’s system constraints (bottlenecks decide the overall constraint), and it the biggest point of failure when it comes to effective capacity planning. This is where time granularity plays a fundamental role. Data granularity for 24-month plan very different to data granularity for the next 60 days or two weeks plan.

The second fundamental aspect with respect to creating an effective capacity plan is optimization: to determine an optimum plan within defined capacity.

Most organizations fail to create optimal capacity plans, they just fail to integrate it with feasibility. MRP execution adopts infinite capacity and its outcome is an unfeasible plan fuelling chaotic management. Many don’t have adequate planning systems, or many have invested millions but with poor or limited usage.

An optimal plan allows organizations to maximize or minimize the objectives they are trying to meet such as satisfying demand within different capacity constraints variants (shift definition) that have corresponding cost implication.

The optimal and feasible plan should highlight demand that cannot be satisfied and must be feedback to demand management. Demand management must have a clear understanding of what can be realized and what is not feasible in terms of products, markets, and timing).

The value of an optimal and feasible plan is also a critical feedback to demand management:

·         Unconstrained demand versus constrained demand by different capacity variants and cost implication

·         This then enable marketing to have clear view demand profiles versus supply profiles and their impact on feasibility and profitability

For an organization to be able to generate optimal and feasible plan it requires effective Supply Chain Governance Framework (SCGF) and supporting planning systems (IT architecture) that can generate optimal plans and provide clear performance guidance in terms of what it has planned versus actual outcome. This is fundamental for learning and adaptation.

Most organization do not have effective governance in place, most have poor understanding in  dealing with constraints and most have close to zero initiative to maximize potentiality.

Effective Supply Chain governance must co-exist with system governance (the whole system): it is of no value to having an effective SCGF in place while the system is a disaster. Nokia Supply Chain governance might be effective, but it will not change the destiny of Nokia due to its disastrous governance.

Nokia ex CEO: ‘We did not do anything wrong but somehow we lost’ : simply stated it things the right way, but it failed to do the right things. Both the right things and wrong things are perfectly correct with respect to theory (all covered within MBA) but from system perspective to ensure viability it is imperative to always strive to do the right things that achieve system balance (efficiency and effectiveness)

The SCGF must be supported by smart Supply Chain Planning System (SCPS) that are able to generate optimal plans within the capacity constraints which are feasible. The SCPS must be able to generate plans that are aligned with time granularity (planning rolling waves) and respective feasibility:

• 1 to 4 year constrained plan by product family/market/facility based on expected demand and facility constrains, projected investment projection (shut down, new facilities or consolidation)
• 12 months constrained and optimal plan (network plan) by product/facility/supplier as per demand requirements (forecasting and marketing initiatives) matched by key resource capacity variants (shifts) which is fundamental for shift planning (increase or decrease)
• The selected 12-month plan (rolling wave review every 3 months) driving sourcing and procurement rolling into the production plan
• The time granularity for actual production: example 3 month window (qty based on lot size rules for batch size and rough-cut scheduling) and detailed scheduling production plan 3-4 weeks within exact constrains, routings (operations and BoM assignment) and sequence optimization

·         To absorb demand flexibility and protect detail scheduled plans the use of rule based available to promise systems (gATP) can deal with flexibility without disturbing feasible and optimal plans. This will then ensure customer delivery is met in full and on time and must where required not fulfill demand or rather postpone demand that is not covered within the demand characteristics used by optimum and feasible plan.

Many organizations have invested millions in Supply Chain Planning Systems and ERP, some with success while others with dismal results.

Fundamental to understand that ERP system utilize MRP logic which generates chaotic planning results: it cannot generate feasible and optimum plans resulting in a chaotic situation. Some organization have heavily invested in Supply Chain Planning System such as SAP APO that not only have MRP type deterministic heuristics but also optimization toolset to enable optimum planning such as linear programming that permit defining objective function to maximize profit or service levels.

Majority organizations have failed to utilize SAP APO toolset correctly such as the SNP optimizer which utilizes linear programming techniques to achieve feasible and optimum plans with corresponding scenario as per defined objective function. Many do not feedback to Demand Management constrained supply: marketing assumes demand will be always matched. The SNP optimizer is a critical toolset to be able to create scenarios with different capacity variants and their corresponding cost implication.

Many have made substantial investment SCPS with poor result not due to system capability but due to lack of adequate and effective Supply Chain Governance Framework in place that is able to manage potentiality, system complexity, system dynamics feedback that causes system imbalance or sub-optimum outcome (less than ideal efficiency and effectiveness). Many fail to plan with the correct data set that considers time granularity and where data granularity flows to different data sets: Sales and Operation Plan that flows into Masters Production Schedule (MPS)  network plan, MPS that flow into detailed production plan by site by product , that flows into detailed scheduled production plan.

Many have invested in Sales and Operation Planning System (ideal for 1-4 year planning rough cut) but without an effective integration to SCPS that is able to use output of S&OP time granularity plan to a more detailed supply chain network plan which feasible and optimum plan in detail over next 12-month horizon.

This is critical for feedback, without feedback tools such as S@OP and demand management are of little value.

Feedback is critical to provide a view of what has occurred (actual) versus what was planned in terms of feasible (constrained) and optimum: this is critical to ensure that what is planned in terms of feasible and optimum is realized and is critical for learning and adaptation in order carry-out corrective action.

Finally, many have invested million in reporting data warehouse system but in general they are ‘so what’ performance indicators reducing the ability to true learning, understanding, and adaptation. Inventory KPI or on-time delivery, or backorders, equipment effective KPI in isolation provide limited value.

Concluding remarks:

Creating feasible (constrained) and optimum plans will leverage performance, but it requires effective Supply Chain Governance Framework and effective Supply Chain Planning System in place.

SAP APO Supply Chain Planning System toolset provided more than adequate tools sets to generate feasible and optimum plans, with the capability to deal with flexibility such as rule-based gATP (global available to promise) but sadly SAP has decided to stop further development (end of support planned for 2025).  SAP APO will be replaced by a cloud-based tool called IBP:

·         IBP for Sales and Operations planning

·         IBP for demand management

·         IBP for order based

The optimization functionality that was available in APO SNP optimizer will not be available in IBP. SNP utilized optimization server containing iLOG toolset to enable optimization planning which was then fed back to SNP scenario for final scenario adoption.

Production planning (PPDS) critical for short term detailed production planning will not be available in IBP, clients need to migrate to SAP 4/H and activate Advanced Planning. Rule-based gATP will not be available in IBP but rather SAP 4/H and Advanced Available to Promise activated: at the time of writing AAP does not have the same capability as per rule based gATP in APO.

Cloud-based SCPS solution may be less costly but one critical aspect to consider is that they are very ‘vanilla’ type allowing limited customer modification and fit for purpose. Supply Chain Planning systems to work effectively need to support supply chain complexity and must not be a constraining factor due to its functionality. SAP APO offered a variety of toolset to enable ‘customer’ specific adaptation.