SKU Proliferation and Plant Performance
Harbour Foods Ltd operates a single food-processing plant with three filling lines. Over three years, active SKUs rose from 40 to 96, mostly small-volume variants. On-time-in-full delivery has fallen to 82% against a 95% customer target, while average changeover time is 5.5 hours against a 2-hour engineering benchmark. Overall equipment effectiveness is 58%, with changeover and minor stops the largest losses. Forecast error at SKU level is 28%, inventory has risen to 78 days against a 45-day target, and expedited freight costs are three times the prior-year level. Sales incentives reward revenue volume only. The operations director proposes banning all SKU rationalisation until customer complaints are resolved; the commercial director rejects any SKU cuts. The CEO asks you to lead a review and recommend a performance management and operating response.
1. Diagnose the root causes of the plant's performance problem and propose a balanced set of performance measures for the CEO.
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Diagnosis. The symptoms are connected, not separate. SKU growth from 40 to 96 fragments production runs, drives the 5.5-hour changeovers and increases scheduling complexity. With 28% SKU-level forecast error, the plant holds 78 days of inventory to protect service, yet still misses 95% OTIF because the wrong SKUs are available. Expedited freight is a symptom of planning failure, not a transport problem. OEE at 58% is being managed as a single number, so changeover and minor-stop losses are visible but not owned. Sales incentives reward volume, so commercial teams add variants without bearing inventory or changeover cost.
Measures. Use a small scorecard: OTIF by customer and SKU family; schedule adherence; changeover time by line and product family; OEE with loss categories; forecast bias and absolute error at family level; inventory days and obsolete stock; expedited freight cost; and contribution margin after changeover and inventory costs. Review weekly at plant level and monthly with sales. The key governance change is to make trade-offs explicit: no SKU or promotion should be approved without a capacity, inventory and margin assessment. The operations director's proposed ban on rationalisation and the commercial director's refusal to cut SKUs both avoid the trade-off the scorecard should expose.
2. Recommend a 90-day SKU and changeover plan that addresses commercial resistance.
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Recommendation. Do not start with a blanket SKU ban. Build a Pareto fact base: volume, contribution margin, changeover cost, forecast error and customer concentration by SKU. Classify into runners, repeaters and strangers. Protect contracted and strategically important lines; place a temporary freeze on new SKU introductions; and phase out the bottom tail only after customer-by-customer review.
90-day sequence. Days 1 to 15: joint commercial-operations task force, data pack and agreed decision rules. Days 16 to 30: pilot quick changeover on one line targeting 3.5 hours then 2.5 hours; publish results. Days 31 to 60: remove or consolidate the lowest-value 15% of SKUs with account plans for affected customers; align sales incentives to contribution margin and forecast accuracy, not revenue alone. Days 61 to 90: lock a monthly SKU governance gate, review service and inventory results, and scale changeover gains to other lines.
Commercial handling. Give sales a veto only with a written margin and service case; escalate unresolved cases to the CEO. Communicate customer-specific continuity plans. Measure success by OTIF, inventory days, changeover hours and margin, not by the number of SKUs cut.