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# KPIs & Metrics

You manage what you measure — and in IBP, metrics are the mechanism that turns cross-functional alignment from an aspiration into an observable reality. Without a shared scorecard, every function optimizes for its own definition of success, and the integrated plan fragments before the month is over. 🎯

Good IBP metrics do three things: they drive behavior, they create accountability, and they surface trade-offs early enough to act on them. When everyone is looking at the same numbers, disagreements become productive trade-off conversations rather than finger-pointing exercises.

# Metric Categories

  • Forecast Accuracy (MAPE) — The average absolute percentage error between forecast and actuals. The most common demand metric, but watch for the limitations of MAPE at low volumes.
  • Forecast Bias — Whether the organization systematically over- or under-forecasts. Bias is more actionable than accuracy because it reveals structural problems.
  • Demand Plan Adherence — How closely the consensus demand plan matches actuals, measured after management adjustments.
  • Forecast Value Added (FVA) — Does each step in the forecasting process actually improve accuracy? If not, it is adding noise, not value.
  • Schedule Adherence — The percentage of planned production completed on time and in the planned quantity. Misses cascade directly into inventory shortfalls and service failures.
  • Capacity Utilization — Actual output versus available capacity. High utilization looks efficient but leaves no buffer for variability.
  • Supplier OTIF (On-Time In-Full) — The percentage of purchase orders received from suppliers both on time and in the correct quantity.
  • Days of Supply (DOS) — How many days of forward demand current inventory could cover.
  • Inventory Turns — How many times inventory is sold and replaced over a period. Higher turns mean less capital tied up.
  • Obsolescence Rate — Inventory written off due to expiry, damage, or demand that never materialized. A lagging indicator of poor lifecycle management.
  • Inventory Plan Adherence — Actual inventory levels versus plan. Persistent overages indicate demand misses or supply overproduction.
  • Customer OTIF — Orders delivered both on time and in full. The single most important service metric in most IBP implementations.
  • Fill Rate — Demand fulfilled from available stock at time of order. Measures availability without the timing dimension.
  • Perfect Order Rate — Orders delivered on time, in full, with correct documentation, and without damage. The most comprehensive service metric.
  • Revenue vs. Plan — Actual revenue compared to the IBP financial projection. The starting point for gap analysis.
  • Margin vs. Plan — Gross or contribution margin versus plan. Revenue can hit target while margin erodes due to mix or cost changes.
  • Cost Variance — Actual supply chain costs versus plan, including manufacturing, logistics, and procurement.
  • Working Capital — Inventory investment plus receivables minus payables. The financial expression of inventory health.

# Key Formulas 

\displaystyle \text{MAPE} = \frac{1}{n} \sum_{i=1}^{n} \left| \frac{A_i - F_i}{A_i} \right| \times 100
\displaystyle \text{Inventory Turns} = \frac{\text{COGS}}{\text{Average Inventory Value}}
\displaystyle \text{Customer OTIF} = \frac{\text{Orders delivered on-time} \cap \text{in-full}}{\text{Total orders}} \times 100
\displaystyle \text{Days of Supply} = \frac{\text{On-Hand Inventory}}{\text{Average Daily Demand}}

# Building an IBP Scorecard

A scorecard with 50 metrics is not a scorecard — it is a data dump. Effective IBP scorecards contain 8 to 12 metrics that tell the complete story across demand, supply, inventory, customer, and financial dimensions.

Selection principles:

  1. Balance across functions — At least one metric from each category. Skewing toward any single function creates blind spots.
  2. Mix leading and lagging — Lagging metrics confirm what happened; leading metrics predict what will happen. You need both.
  3. Ensure actionability — Every metric should have a clear owner and a defined response when performance drifts outside tolerance.
  4. Avoid redundancy — Inventory turns and days of supply measure similar things. Pick one.
  5. Align to strategy — If the business strategy emphasizes service, weight service metrics. If cost efficiency, weight financial and inventory metrics.

# Leading vs. Lagging Indicators

Type Definition Examples Use in IBP
Leading Predicts future performance Forecast bias trend, supplier lead time changes, capacity utilization Enables proactive decisions; flags risks before they hit results
Lagging Confirms past performance Revenue vs. plan, customer OTIF, obsolescence write-offs Validates whether plans and actions delivered results

The mistake most organizations make is building a scorecard entirely of lagging indicators. By the time you see a customer OTIF miss, the root cause happened weeks ago. Leading indicators give the planning team time to respond.

# Metric Alignment

Departmental KPIs should ladder up to IBP-level KPIs, not conflict with them. Misaligned incentives are one of the most common reasons IBP processes stall.

When sales is rewarded for revenue volume and finance is rewarded for margin improvement, the IBP process becomes a negotiation between competing objectives rather than a collaborative planning exercise. Metric alignment does not mean everyone has the same KPI — it means everyone's KPIs point in the same direction.

# Common Metric Traps

  1. Vanity metrics — Metrics that look impressive but do not drive action. Aggregate forecast accuracy can mask severe misses at the SKU level. Always measure at the level where decisions are made.
  2. Conflicting KPIs — Sales rewarded for volume; finance for cost reduction; operations for utilization. These conflicts play out in every IBP meeting until incentives are realigned.
  3. Measuring too many things — When everything is a KPI, nothing is a KPI. Diluted focus means no single metric gets the ownership it requires.
  4. Measurement without consequence — Tracking metrics every month but never changing the process when performance consistently underperforms. Metrics without accountability are just reports.

# Comprehensive Metric Reference

Metric Formula / Definition Category Lead/Lag Typical Target
Forecast Accuracy 1 - MAPE Demand Lagging 70–85%
Forecast Bias Sum(F-A) / Sum(A) Demand Leading Within +/- 5%
Customer OTIF On-time AND in-full / total orders Customer Lagging 95–98%
Fill Rate Demand filled from stock / total demand Customer Lagging 97–99%
Perfect Order Rate Zero-defect orders / total orders Customer Lagging 90–95%
Schedule Adherence Planned production completed on time Supply Lagging > 95%
Capacity Utilization Actual output / available capacity Supply Leading 80–90%
Supplier OTIF POs received on-time and in-full Supply Leading > 95%
Inventory Turns COGS / average inventory value Inventory Lagging Industry-dependent
Days of Supply On-hand / average daily demand Inventory Leading Category-dependent
Revenue vs. Plan Actual / planned revenue Financial Lagging Within +/- 3%
Margin vs. Plan Actual / planned margin Financial Lagging Within +/- 2%

# Further Reading

  • Forecast Accuracy — Deep dive into measuring and improving forecast performance.
  • Financial Planning — How financial metrics connect to the broader IBP financial reconciliation process.
  • Demand Planning — The upstream process that drives demand-side metrics.