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Reducing Delays and Improving Operations in an SME

By Revised edition published Professional profileOriginal first-publication date not documented.

A fictional operations case illustrating how to reduce order delays, clarify responsibilities and measure process improvements.

Conceptual business photograph illustrating a management case study
Illustrative editorial composition; not an actual photograph of the business case.
English adaptation: This page may provide a shorter overview than the Portuguese original. For the complete text and additional detail, consult the Portuguese version.

Context and business challenge

A fictional technical-materials distributor with 18 employees receives about 120 orders each month. Customer complaints, duplicated administrative work and poorly assigned responsibilities delay deliveries. Order information is dispersed across spreadsheets and email, making it difficult to identify recurring bottlenecks.

Transparency:This fictional case is provided for education only. It does not represent an actual company, client project, achieved result or consulting engagement.

Initial data and assumptions

The initial illustration assumes 120 monthly orders, an average processing time of nine days and an 18% rework rate; the proposed target is six days. Before setting a target, verify how these measures are defined and whether the period and data sources are comparable.

Orders per month120
Average order preparation time9 days
Orders requiring rework18%
Target average preparation time6 days
Target rework rateUp to 10%

Swipe horizontally to view all columns.

How to investigate the causes

Map the whole process, from receipt of an order to dispatch. Identify duplicate approvals, waiting times and missing information. Categorise delays by cause, such as stock availability, incomplete customer instructions or internal validation. Examine the distribution of processing times as well as the average, since extreme delays may be concealed by a single mean.

  1. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  2. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  3. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.

Quantitative analysis

At an 18% rework rate, 120 orders imply an average of 21.6 cases of rework per month; a 10% rate would imply 12. The indicative improvement is nearly ten fewer cases per month. Reducing the average processing time from nine to six days corresponds to a 33.3% reduction. These are analytical targets, not benefits already achieved.

Proposed action plan

Define mandatory information at order intake, nominate a person responsible for each stage, and establish escalation rules for blocked decisions. Maintain a weekly board of overdue orders with causes and corrective actions. Run a six-week pilot in one team, checking quality and workload before extending the new process.

  1. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  2. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  3. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  4. Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.

Monitoring indicators

Measure average and 90th-percentile processing time, the proportion of orders requiring rework, on-time deliveries and complaints per 100 orders. Reviewing all four prevents an apparently faster process from hiding poorer service for a minority of customers.

  • Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  • Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.
  • Orders delivered on time
  • Four fictional cases showing structured business analysis and decision-making, with explicit assumptions, calculations and limitations.

Risks and limits of the analysis

An improvement in the mean processing time does not necessarily improve the customer experience. Avoid shifting delays to other parts of the process or creating quality problems. Assess costs, customer satisfaction and accuracy alongside speed.

Explore Risks and limits of the analysisCase takeaway: the aim is to make operations more predictable. The example does not claim that a company achieved the targets: all figures are working assumptions.

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