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Home » Blogs » Think Tank » Three Metrics to Help Manage Supply-Chain Uncertainty

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Three Metrics to Help Manage Supply-Chain Uncertainty

March 1, 2021
Serge Ratmiroff, SCB Contributor

As the COVID-19 pandemic continues to disrupt business operations, customer demand and cash flow, there's a case for monitoring and incentivizing compliance with key performance indicators (KPIs) to drive results and manage uncertainty.  

Regardless of where your company sits within the supply-chain ecosystem, managing risk and disruption requires prioritization of three key metrics.

Forecast Accuracy

Forecasting impacts procurement of long lead time materials, line scheduling and changeovers, inventory levels, overall cost structure and profitability. As a rule, forecasting involves sales and shipment history to drive a statistical baseline forecast that can then be adjusted via causal factors, such as customer collaboration, promotions and third-party macroeconomic or industry research. However, the pandemic’s disruption has made statistical forecasts unreliable indicators of demand. Even prior to the pandemic, achieving high forecast accuracy has been and continues to be challenging. What enablers can be deployed to support this metric?

  • Organizational change management (OCM): A proven approach to managing this high level of demand uncertainty is to incentivize your sales personnel to strive for higher forecast accuracy. This implies monitoring and rewarding higher levels of customer collaboration focusing on higher margin products, if possible.

Ultimately, a formal process for reaching a consensus for unconstrained and constrained forecasts is required that is based on your sales team’s best estimation of future sales order flow.

  • Business 4.0 technology: The I.T. enabling platform must support strong statistical forecasting, customer collaboration, forecast simulations, cognitive analytics (artificial intelligence and machine learning) and integrated sales and operations planning (S&OP) business processes.

Manufacturing Schedule Compliance

As a rule, the manufacturing schedule is driven by a process whereby an unconstrained forecast is capacity leveled and optimized for supply constraints. This results in a constrained demand plan that is then adjusted as needed via the S&OP process to reach a consensus schedule. The production lines are sequenced via multiple criteria to minimize changeovers and maximize throughput. Surprisingly, it is not uncommon to find that compliance to the manufacturing schedule is much lower than planned. Lack of compliance may be driven by inconsistent KPI reward systems that allow operations teams to opt out to maximize production output.

Again, two enablers will drive a higher KPI metric. 

  • OCM: Monitoring and rewarding schedule compliance. 
  • Tech: The I.T. platform must support high planning efficiency and effectiveness. For example, ERP systems run MRP using a real-time memory-resident transactional database that supports rule-based or optimization algorithms. The net result you are striving for is planning your supply chain quickly while automating capacity leveling and line sequencing to maximize throughput. 

Purchasing Schedule Compliance

The purchasing schedule is also driven by the S&OP process outlined above. The pandemic has been a significant contributor to lower-than-planned performance by suppliers, subcontractors and contract manufacturers across industries. In some extreme cases, the integrity of the supplier network may be impacted to the point of compromising the entire enterprise’s business continuity.

Managing these KPIs in times of crisis can be overwhelming, but a pragmatic action plan that incentivizes your team is a solid first step in confronting and overcoming any challenges.

In the short term, you'll gain additional insight to your business operation to help you cope with disruption — and begin the journey toward profitable resilience.

Serge Ratmiroff is director of global supply-chain consulting at Tata Consultancy Services.

Global Supply Chain Management Quality & Metrics

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