# Field Project Report: [Client organisation] [Project title]

> Final report of an MBA action-learning or consulting field project for
> a real client organisation: executive summary, situation, approach,
> findings with exhibits, recommendations, implementation roadmap and
> client sign-off. It is written for the client's decision maker first and
> for the faculty advisor second, and it answers the key question agreed
> in the statement of work (`mba/mba-field-project-sow`). Source basis:
> the pyramid principle for business writing (Minto 1987), action learning
> (Revans 1980), standard capital budgeting (NPV, IRR, payback) and common
> consulting report practice, all in original words. Your school's course
> handbook and the client agreement take precedence on format, length and
> confidentiality. Replace every `[bracketed]` value and every row marked
> *Example*. This is a report format, not financial, legal or investment
> advice.

<!--
Guidance: How to use this template
- Start from the signed SOW. Copy the key question into section 2 word
  for word; the report is graded and judged on whether it answers that
  question.
- Write the executive summary last and put it first. A busy sponsor
  should be able to stop after one page and still know what to do,
  why, what it costs and what happens first.
- Every number in an exhibit carries its source (client dataset,
  survey, assumption ID) and reconciles to the client's own figures.
  Agree the baseline with the client's finance team before the final
  presentation.
- The worked example continues the Northfield Outdoor Co. project from
  the SOW template: a fictional outdoor-gear retailer with stores and
  e-commerce, studying the cost of online returns. All numbers are
  invented and were computed for this template.
- Related templates: Field Project SOW (`mba/mba-field-project-sow`),
  Capstone Project Report (`mba/mba-capstone-project-report`), Group
  Project Report (`mba/mba-group-project-report`), Case Write-up
  (`mba/mba-case-write-up`), NPV and IRR card (`mba/mba-npv-irr-card`),
  Business Communication card (`mba/mba-business-communication-card`),
  Peer Feedback (`mba/mba-peer-feedback`), Learning Journal
  (`mba/mba-learning-journal`), and the practitioner templates Executive
  Summary (`business/executive-summary`), Business Case
  (`business/business-case`) and Investment Appraisal
  (`finance/investment-appraisal`).
-->

## Document control

<!-- Guidance: Use the same Document ID family as the SOW so the two documents are traceable. Classification follows the NDA: most client reports are confidential, and a separate anonymised version is prepared if the school wants to keep or share it. -->

| Field | Value |
|---|---|
| Document ID | [FP-RPT-001] |
| Related SOW | [FP-SOW-001, version 1.1] |
| Project title | [Reducing the cost of online returns] *(Example)* |
| Client organisation | [Northfield Outdoor Co.] *(Example, fictional)* |
| Client sponsor | [Name, title] |
| Course or programme | [Course code and name, term] |
| Faculty advisor | [Name] |
| Student team | [@student-1], [@student-2], [@student-3], [@student-4] |
| Data period analysed | [Last two financial years] *(Example)* |
| Currency and units | USD unless stated *(Example)* |
| Version | [1.0] |
| Status | [Draft / Client review / Final / Accepted] |
| Last updated | YYYY-MM-DD |
| Classification | [Confidential: client, team and faculty only] |

### Approvals

| Role | Name | Decision | Date |
|---|---|---|---|
| Student team lead (for the team) | [@student-1] | [Submitted] | YYYY-MM-DD |
| Faculty advisor | [Name] | [Reviewed] | YYYY-MM-DD |
| Client sponsor | [Name] | [Accepted, see section 9] | YYYY-MM-DD |

## Contents

- [1. Executive summary](#1-executive-summary)
- [2. Key question and scope](#2-key-question-and-scope)
- [3. Situation](#3-situation)
- [4. Approach](#4-approach)
- [5. Findings](#5-findings)
- [6. Options considered](#6-options-considered)
- [7. Recommendations and business case](#7-recommendations-and-business-case)
- [8. Implementation roadmap](#8-implementation-roadmap)
- [9. Client sign-off and handover](#9-client-sign-off-and-handover)
- [10. Team reflection (academic annex)](#10-team-reflection-academic-annex)
- [11. Quality checklist and common mistakes](#11-quality-checklist-and-common-mistakes)
- [12. Appendix: data, assumptions and calculations](#12-appendix-data-assumptions-and-calculations)
- [Sources and further reading](#sources-and-further-reading)
- [Revision history](#revision-history)
- [Standard and licence note](#standard-and-licence-note)

## 1. Executive summary

<!-- Guidance: One page. Answer first, then three supporting points, then the money, then the first step. Use the pyramid structure: the governing thought at the top, grouped reasons below (Minto 1987). Pitfall: a summary that narrates what the team did instead of what the client should do. -->

**Answer.** [One or two sentences: what the client should do and what it achieves.]

**Why** (three supporting points, each backed by an exhibit):

1. [Finding and exhibit reference]
2. [Finding and exhibit reference]
3. [Finding and exhibit reference]

**Economics.** [One-off cost, annual net saving, NPV, payback.]

**First step.** [What happens in the next 30 days, and who owns it.]

*Example*:

**Answer.** Northfield should launch three changes in the next 12 months: fit guidance on apparel and footwear product pages, free in-store returns for online orders, and grading and resale of returned camping equipment. Together they cut the direct cost of online returns by about USD 0.43m a year before running costs and USD 0.33m after them, exceeding the USD 250,000 target, for a one-off cost of USD 285,000.

**Why**:

1. Apparel and footwear produce 82.8% of online returns, and size or fit is the stated reason for 52% of them (Exhibits 2 and 3).
2. 34.9% of surveyed online customers both live within 20 minutes of a store and would choose a store return, which cuts the shipping cost of those returns from USD 8.50 to about USD 2.00 (Exhibit 4).
3. Returned camping equipment carries the highest write-down (USD 22 per return), and most of it is resaleable after grading (Exhibit 2, warehouse observation).

**Economics.** Three-year NPV USD 347,700 at Northfield's 10% hurdle rate, IRR 60.1%, payback about 1.5 years (Exhibit 6).

**First step.** The Vice President of E-commerce approves the fit-guidance vendor selection and a four-store returns pilot by [date]; the head of e-commerce owns both.

## 2. Key question and scope

<!-- Guidance: Restate the key question from the signed SOW exactly, and list any approved change requests. If the question changed during the project, say so and why. -->

| Item | Content |
|---|---|
| Key question (from SOW) | [Copy from SOW section 3] |
| In scope | [Summary of SOW section 4] |
| Out of scope | [Summary] |
| Approved change requests | [CR IDs and one-line description] |

*Example*: Key question: which changes should Northfield make in the next 12 months to reduce the annual cost of online returns by at least USD 250,000 without reducing online conversion or customer satisfaction below current levels? In scope: online orders and returns, all four categories, product-page, routing and resale options. Out of scope: store-purchased returns, carrier contracts, software build, legal review of policy wording. Change request CR-01 added exchange options to the option long list.

## 3. Situation

<!-- Guidance: Give the reader just enough context to follow the findings: the business, what changed, why it matters now. Facts with sources, no adjectives. Half a page. -->

*Example*: Northfield Outdoor Co. sells outdoor apparel, footwear, camping equipment and accessories through 38 stores and an e-commerce site. Online orders reached 420,000 last financial year at an average order value of USD 96, giving online revenue of about USD 40.3m. Two years ago Northfield introduced free mail returns to match larger online sellers. Return volume has since grown faster than orders, and the finance team estimates the direct cost of returns (return shipping, warehouse processing and write-downs on returned stock) at USD 1.84m a year, 4.57% of online revenue. The topic is urgent because the budget for next year is set in [month] and the leadership team has asked for options that do not undermine the free-returns promise.

**Exhibit 1. Online business at a glance** *(Example)*

| Metric | Value | Source |
|---|---|---|
| Online orders | 420,000 | Order data, last FY |
| Average order value | USD 96 | Order data |
| Online revenue | USD 40,320,000 (`=420000*96`) | Computed |
| Online returns | 77,070 | Returns data |
| Return rate | 18.35% (`=77070/420000`) | Computed |
| Direct cost of returns | USD 1,840,629 | Exhibit 2 |
| Returns cost as share of online revenue | 4.57% (`=1840629/40320000`) | Computed |

## 4. Approach

<!-- Guidance: Show the method in a diagram and a short table: what you did, with whom, and how much evidence it produced. The faculty advisor grades rigour here; the client wants to know it is trustworthy. -->

```mermaid
flowchart LR
  A["Kick-off and SOW"] --> B["Hypotheses H-01 to H-05"]
  B --> C["Diagnosis: returns and cost data"]
  B --> D["Customer research: interviews and survey"]
  C --> E["Option long list (11 options)"]
  D --> E
  E --> F["Screening: impact, cost, customer risk"]
  F --> G["Business case for 3 options"]
  G --> H["Roadmap and KPIs"]
  H --> I["Final report and sign-off"]
```

| Evidence | Volume | Use |
|---|---|---|
| Order and return lines, two financial years *(Example)* | 420,000 orders and 77,070 returns in the last year | Baseline, category and reason analysis |
| Finance cost build-up *(Example)* | Shipping, processing and write-down per return by category | Cost exhibit |
| Internal interviews *(Example)* | 9 (e-commerce, merchandising, warehouse, stores, finance, customer service) | Process map, option ideas |
| Customer interviews *(Example)* | 12 | Reasons for returning, reactions to options |
| Customer survey *(Example)* | 312 responses | Store-return preference, fit-tool interest |
| Warehouse observation *(Example)* | 2 shifts | Grading and write-down process |

Hypothesis results:

| ID | Hypothesis | Result | Evidence |
|---|---|---|---|
| H-01 *(Example)* | Most returns are apparel and footwear, driven by size and fit | Supported | Exhibits 2 and 3 |
| H-02 *(Example)* | Fit guidance can avoid a quarter of size and fit returns | Partly supported: 25% used as the base case, tested in a pilot | Assumption A-02 |
| H-03 *(Example)* | Customers near a store would return in store | Supported | Exhibit 4 |
| H-04 *(Example)* | Camping equipment is written off too often | Supported | Exhibit 2, observation |
| H-05 *(Example)* | A mail-returns fee would cost more in conversion than it saves | Supported (stated intent), option not recommended | Survey |

## 5. Findings

<!-- Guidance: One finding per subsection, written as a full-sentence headline that states the insight ("Apparel and footwear drive 83% of returns"), followed by the exhibit and two or three sentences of interpretation. Pitfall: headlines that only label the chart ("Returns by category"). -->

### 5.1 Apparel and footwear drive 83% of returns and 79% of their cost

**Exhibit 2. Online returns and direct cost by category, last FY** *(Example)*

| Category | Orders | Return rate | Returns | Cost per return (USD) | Returns cost (USD) | Share of returns | Share of cost |
|---|---|---|---|---|---|---|---|
| Apparel | 168,000 | 26% | 43,680 | 21.70 | 947,856 | 56.7% | 51.5% |
| Footwear | 84,000 | 24% | 20,160 | 24.70 | 497,952 | 26.2% | 27.1% |
| Camping equipment | 105,000 | 9% | 9,450 | 34.70 | 327,915 | 12.3% | 17.8% |
| Accessories | 63,000 | 6% | 3,780 | 17.70 | 66,906 | 4.9% | 3.6% |
| **Total** | **420,000** | **18.35%** | **77,070** | **23.88** | **1,840,629** | **100%** | **100%** |

Cost per return = return shipping USD 8.50 + warehouse processing USD 4.20 + write-down per return (apparel USD 9, footwear USD 12, camping equipment USD 22, accessories USD 5), from the finance cost build-up. Excel for a row: returns `=B2*C2`, cost `=D2*E2`; total rate `=SUM(D2:D5)/SUM(B2:B5)`; average cost per return `=F6/D6`.

Apparel and footwear together account for 63,840 returns (82.8%, `=63840/77070`) and USD 1,445,808 of cost (78.5%, `=1445808/1840629`; the rounded category shares in Exhibit 2 add to 78.6%). Camping equipment has a low return rate but the highest cost per return, because returned tents and stoves are often written down without inspection.

```vega-lite
{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
  "description": "Exhibit 2 chart: direct cost of online returns by category, USD (Example, fictional data)",
  "width": "container",
  "height": 220,
  "data": {"values": [
    {"category": "Apparel", "cost": 947856, "returns": 43680},
    {"category": "Footwear", "cost": 497952, "returns": 20160},
    {"category": "Camping equipment", "cost": 327915, "returns": 9450},
    {"category": "Accessories", "cost": 66906, "returns": 3780}
  ]},
  "mark": "bar",
  "encoding": {
    "y": {"field": "category", "type": "nominal", "sort": "-x", "title": null},
    "x": {"field": "cost", "type": "quantitative", "title": "Returns cost (USD)"},
    "tooltip": [
      {"field": "category", "type": "nominal"},
      {"field": "returns", "type": "quantitative", "format": ","},
      {"field": "cost", "type": "quantitative", "format": ","}
    ]
  }
}
```

### 5.2 Size or fit is the reason for about half of apparel and footwear returns

**Exhibit 3. Stated reason for apparel and footwear returns, last FY** *(Example)*

| Reason code | Share | Returns (rounded) |
|---|---|---|
| Size or fit | 52% | 33,197 |
| Not as described | 17% | 10,853 |
| Changed mind | 14% | 8,938 |
| Defective | 8% | 5,107 |
| Other | 9% | 5,746 |
| **Total** | **100%** | **63,840** (rows rounded) |

Reason codes are chosen by customers in the returns portal, so they are noisy; customer interviews confirmed that "too small" and "runs large" complaints cluster in a small number of brands and footwear lasts. 9 of 12 interviewed customers said they had ordered two sizes to keep one ("bracketing").

### 5.3 About a third of online customers would return in a store

**Exhibit 4. Store-return preference, customer survey** *(Example)*

| Measure | Count | Share |
|---|---|---|
| Respondents | 312 | 100% |
| Live within 20 minutes of a store | 178 | 57.1% of respondents |
| Of those, would choose a store return | 109 | 61.2% of those near a store |
| Near a store and would choose a store return | 109 | 34.9% of respondents (`=109/312`) |

The base case assumes 35% of remaining returns move to stores (assumption A-03). The survey sample came from customers who had ordered in the last six months and opened the survey email, so it may over-represent engaged customers; the pilot in section 8 tests the rate before a full launch.

### 5.4 Charging for mail returns is not worth the customer risk

Survey respondents who had ordered more than three times a year were the most likely to say they would shop elsewhere if mail returns carried a fee, and they generate a disproportionate share of online revenue. Because the other three options meet the target without touching the free-returns promise, the team did not recommend a fee. This finding is based on stated intent, which overstates real behaviour; it is recorded as an option for a later test.

## 6. Options considered

<!-- Guidance: Show that the recommendation beat real alternatives. Screen a long list against explicit criteria, then cost the short list. Pitfall: a long list of straw men. -->

| ID | Option | Impact on cost | One-off cost | Customer risk | Decision |
|---|---|---|---|---|---|
| O-01 *(Example)* | Fit guidance on apparel and footwear pages | High | Medium | Low | Short-listed (R1) |
| O-02 *(Example)* | Free in-store returns for online orders | High | Low | Low (positive) | Short-listed (R2) |
| O-03 *(Example)* | Grading and resale of camping returns | Medium | Low | None | Short-listed (R3) |
| O-04 *(Example)* | Fee for mail returns | High | Low | High | Rejected (section 5.4) |
| O-05 *(Example)* | Exchange instead of refund prompt (CR-01) | Medium | Medium | Low | Deferred: needs IT change in the returns portal |
| O-06 *(Example)* | Better product photography for "not as described" items | Medium | High | None | Deferred to the merchandising plan |
| O-07 *(Example)* | Restrict serial returners | Low | Low | Medium | Rejected: small volume, reputational risk |

Four further options (shorter returns window, returnless refunds for low-value items, carrier consolidation, outsourcing grading) were screened out at the first pass; the screening notes are in the appendix.

## 7. Recommendations and business case

<!-- Guidance: Each recommendation is an action with an owner, cost, benefit, KPI and first step. Show the economics with the client's hurdle rate and the Excel formula, so finance can reproduce it. -->

### 7.1 Recommendations

| ID | Recommendation | Mechanism | Owner | KPI |
|---|---|---|---|---|
| R1 *(Example)* | Add fit guidance (size recommendation tool and brand-specific fit notes) to apparel and footwear pages | Avoids 25% of size or fit returns: 8,299 returns a year (`=33197*0.25`, rounded) at USD 22.65 average cost | Head of e-commerce | Size or fit return rate, apparel and footwear |
| R2 *(Example)* | Offer free in-store returns for online orders in all 38 stores | 35% of the remaining 68,771 returns (24,070) move to stores, saving USD 6.50 shipping each (`=8.50-2.00`); gross saving `=(77070-33196.8*0.25)*0.35*6.5` | Head of stores with head of e-commerce | Share of online returns made in store |
| R3 *(Example)* | Grade returned camping equipment and resell grade A and B items | Recovers 40% of the USD 22 write-down on 9,450 returns | Head of logistics | Write-down per camping return |

### 7.2 Economics

**Exhibit 5. Annual savings and costs by recommendation, USD** *(Example)*

| ID | Gross annual saving (steady state) | One-off cost | Annual running cost | Net annual saving (steady state) |
|---|---|---|---|---|
| R1 | 187,955 | 180,000 | 40,000 | 147,955 |
| R2 | 156,454 | 60,000 | 25,000 | 131,454 |
| R3 | 83,160 | 45,000 | 30,000 | 53,160 |
| **Total** | **427,569** | **285,000** | **95,000** | **332,569** |

Gross savings: R1 `=63840*0.52*0.25*22.6474` (average cost per apparel and footwear return `=(947856+497952)/63840`); R2 `=(77070-33196.8*0.25)*0.35*6.5` (24,069.8 store returns before rounding); R3 `=9450*22*0.4`. Year 1 assumes half the steady-state saving because of ramp-up; running costs are paid in full from year 1.

**Exhibit 6. Three-year cash flows, NPV at 10%, IRR and payback, USD** *(Example)*

| ID | Year 0 | Year 1 | Year 2 | Year 3 | NPV at 10% | IRR | Payback (years) |
|---|---|---|---|---|---|---|---|
| R1 | -180,000 | 53,978 | 147,955 | 147,955 | 102,508 | 35.5% | 1.85 |
| R2 | -60,000 | 53,227 | 131,454 | 131,454 | 195,790 | 127.4% | 1.05 |
| R3 | -45,000 | 11,580 | 53,160 | 53,160 | 49,401 | 53.2% | 1.63 |
| **Total** | **-285,000** | **118,784** | **332,569** | **332,569** | **347,700** | **60.1%** | **1.50** |

Excel: year 1 for R1 `=187955*0.5-40000`; NPV `=NPV(10%, C2:E2)+B2` (Excel's `NPV` discounts the first value by one period, so the year-0 outlay is added outside); IRR `=IRR(B2:E2)`; payback interpolates within the year in which cumulative cash turns positive, assuming even cash flow within the year. Total NPV equals the sum of the three NPVs (102,508 + 195,790 + 49,401 = 347,699, difference due to rounding).

**Sensitivity.** R1 carries most of the uncertainty. If fit guidance avoided no returns, R1 would be stopped after the pilot, R2 would then apply to all 77,070 returns (26,974 store returns, gross saving USD 175,334, `=77070*0.35*6.5`), and R2 plus R3 would deliver a net steady-state saving of USD 203,494 a year, below the USD 250,000 target. That is why R1 starts as a pilot with a stop rule (section 8). Re-run the model with your own drivers; see `mba/mba-npv-irr-card` for the method and `finance/investment-appraisal` for a fuller appraisal format.

### 7.3 Risks and mitigations

| Risk | Effect | Mitigation |
|---|---|---|
| Fit tool avoids fewer returns than 25% *(Example)* | Lower R1 saving | A/B test on two brands for 8 weeks before full roll-out; stop rule if avoidance is below 10% |
| Store teams resist handling online returns *(Example)* | Low R2 adoption, poor experience | Store incentive credit for online returns; returns desk process in four pilot stores |
| Resale cannibalises full-price sales *(Example)* | Lower R3 margin | Sell graded items through a separate outlet page with clear grading |
| Customer satisfaction falls *(Example)* | Brand damage | Post-return survey monthly; free mail returns remain available |

## 8. Implementation roadmap

<!-- Guidance: A dated plan with phases, owners, decision gates and KPIs. Start with pilots where the evidence is weakest. Make it something the client can run without the team. -->

```mermaid
gantt
  title Implementation roadmap (Example, 12 months)
  dateFormat YYYY-MM-DD
  axisFormat %b %Y
  section R1 Fit guidance
  Vendor selection and set-up       :r1a, 2027-05-03, 45d
  A/B pilot on two brands           :r1b, after r1a, 56d
  Go or stop decision               :milestone, r1c, after r1b, 0d
  Roll-out to all apparel and footwear :r1d, after r1c, 90d
  section R2 Store returns
  Process design and staff training :r2a, 2027-05-03, 30d
  Pilot in four stores              :r2b, after r2a, 60d
  Roll-out to 38 stores             :r2c, after r2b, 60d
  section R3 Grading and resale
  Grading standard and outlet page  :r3a, 2027-06-01, 45d
  Live resale                       :r3b, after r3a, 180d
  section Review
  Six-month KPI review              :milestone, k1, 2027-11-01, 0d
  Twelve-month KPI review           :milestone, k2, 2028-04-30, 0d
```

| Phase | Months | Actions | Gate | Owner |
|---|---|---|---|---|
| Pilot *(Example)* | 1 to 4 | R1 vendor and A/B test, R2 four-store pilot, R3 grading standard | R1 avoidance at least 10%; R2 store-return share at least 20% in pilot stores | Head of e-commerce |
| Scale *(Example)* | 4 to 9 | R1 and R2 roll-out, R3 live | Customer satisfaction stable; conversion within normal variation | VP E-commerce |
| Embed *(Example)* | 9 to 12 | KPIs in monthly reporting, ownership handed to business-as-usual teams | Twelve-month review against SOW targets | VP E-commerce, finance |

**KPI tree.** Returns cost = return volume x cost per return, minus value recovered. Track return rate by category and reason (R1), store-return share and shipping cost per return (R2), and write-down per camping return (R3), together with the guard-rail KPIs: online conversion rate and post-return satisfaction. At steady state R1 alone lowers the online return rate from 18.35% to about 16.37% (`=(77070-8299)/420000`), just short of the indicative 16.35% return-rate target in the SOW; R2 and R3 cut cost per return rather than volume, and the cost target in the key question (at least USD 250,000) is met.

## 9. Client sign-off and handover

<!-- Guidance: Ask the sponsor to confirm acceptance in writing and record the handover. The sign-off confirms the deliverables were received, not that the client must implement them. -->

| Deliverable (from SOW) | Delivered | Version | Accepted | Comment |
|---|---|---|---|---|
| D-01 Returns baseline and diagnosis | YYYY-MM-DD | [1.0] | [Yes / With comments] | |
| D-02 Customer insight pack | YYYY-MM-DD | [1.0] | [Yes] | |
| D-03 Option evaluation and business case (model) | YYYY-MM-DD | [1.1] | [Yes] | |
| D-04 Final report (this document) | YYYY-MM-DD | [1.0] | [Yes] | |
| D-05 Final presentation | YYYY-MM-DD | n/a | [Yes] | |

**Handover**

- [ ] Model, data dictionary and assumptions log handed to [client owner].
- [ ] Interview notes anonymised or deleted per the SOW data-handling rules.
- [ ] Client data deleted from team storage by YYYY-MM-DD and deletion confirmed to the sponsor.
- [ ] Client consent obtained (or refused) for any classroom use or publication.

**Sponsor statement.** I confirm that the deliverables listed above were received and that this report answers the key question agreed in the statement of work. Acceptance does not commit [client] to implement the recommendations.

| Name | Title | Signature | Date |
|---|---|---|---|
| [Name] | [Title] | | YYYY-MM-DD |

Optional client feedback for the faculty advisor (rate 1 to 5): quality of analysis [ ], usefulness of recommendations [ ], professionalism [ ], communication [ ]. Comments: [ ].

## 10. Team reflection (academic annex)

<!-- Guidance: Most field courses grade reflection separately, often individually. Keep it out of the client version. Use a structured cycle (Kolb 1984; Gibbs 1988) and write about specific moments, not general lessons. -->

Write one entry per team member, or one team entry if the course asks for it. For each, answer:

| Prompt | Response |
|---|---|
| A specific moment that changed our approach | [What happened, when, who] |
| What we expected and what we found | [Contrast] |
| Which course concept helped, and where it did not fit | [Concept and limit] |
| What I would do differently with this client | [Action] |
| What I will carry into my next team or job | [Action] |

*Example fragment (fictional)*: At the mid-point review we presented eleven options; the sponsor asked which three we would bet our own budget on, and we could not answer. We rebuilt the screening around her pilot limit and cut the list in two days. Next time I will ask for the decision maker's constraints in the kick-off, not the mid-point.

Peer evaluation, if required, goes in the course's own form (`mba/mba-peer-feedback`); keep learning notes in `mba/mba-learning-journal`.

## 11. Quality checklist and common mistakes

<!-- Guidance: Run before the draft goes to the sponsor and again before final submission. -->

**Checklist**

- [ ] The executive summary answers the key question in the first sentence.
- [ ] Every finding headline states an insight, and every exhibit has a title, units, source and date.
- [ ] Totals add up; percentages sum to 100% or rounding is noted; the baseline reconciles to the client's finance figure.
- [ ] Each recommendation has owner, cost, saving, KPI and first step.
- [ ] NPV, IRR and payback use the client's hurdle rate and show the Excel formula.
- [ ] The roadmap dates and the Gantt chart agree.
- [ ] Rejected options are explained.
- [ ] Confidential data and interviewee identities are protected as agreed in the SOW.
- [ ] The academic annex is removed from the client version.

**Common mistakes**

1. **Chronological report.** "First we interviewed, then we analysed" buries the answer; lead with the recommendation.
2. **Label headlines.** "Returns by category" says nothing; "Apparel and footwear drive 83% of returns" says what to see.
3. **Unreconciled baseline.** If the client's finance team does not recognise the starting number, nothing after it is believed.
4. **Benefits without costs.** Savings with no running cost or ramp-up overstate the case.
5. **Excel `NPV` misuse.** Including the year-0 outlay inside `=NPV()` discounts it by a year and overstates NPV.
6. **Double counting.** R2 is applied to returns remaining after R1, not to the original volume.
7. **Stated intent taken at face value.** Survey answers about future behaviour need a pilot before a roll-out.
8. **No owners.** A roadmap with "Northfield" as owner of every action will not move.
9. **Overreach.** Recommendations outside the agreed scope (here, carrier contracts) weaken trust in the in-scope ones.
10. **Confidentiality slips.** Customer names in an appendix or client data left in a shared drive after the project.

## 12. Appendix: data, assumptions and calculations

<!-- Guidance: Enough detail for the client's finance team to reproduce every number. Keep raw data outside the report; describe it here. -->

**Assumptions log**

| ID | Assumption | Value | Source | Sensitivity |
|---|---|---|---|---|
| A-01 *(Example)* | Hurdle rate for pilot investments | 10% | Client finance | NPV positive for all three at 10% |
| A-02 *(Example)* | Share of size or fit returns avoided by fit guidance | 25% | Vendor references and interviews; to be tested | Main risk; pilot with stop rule |
| A-03 *(Example)* | Share of remaining returns made in store | 35% | Survey, Exhibit 4 (34.9%) | Pilot target 20% minimum |
| A-04 *(Example)* | Shipping cost of a store return (store-to-warehouse consolidation) | USD 2.00 | Logistics | Saving USD 6.50 per store return |
| A-05 *(Example)* | Write-down recovered by grading camping returns | 40% | Warehouse observation and outlet pricing | |
| A-06 *(Example)* | Year-1 saving as share of steady state | 50% | Ramp-up plan | Running costs in full from year 1 |
| A-07 *(Example)* | Order volume constant over three years | 420,000 | Conservative; growth would raise savings | |

**Data sources**: order lines and return lines exported by the client data lead (pseudonymised), finance cost build-up (version [date]), survey export (312 complete responses), interview notes (anonymised). Survey design notes: `academic/stats-sampling-plan`; for a confidence interval on the store-return share see `academic/stats-confidence-intervals`.

## Sources and further reading

<!-- Guidance: Cite methods, the client's internal sources (by title and date, not content) and any external benchmark. -->

- Minto, B. (1987). *The Pyramid Principle: Logic in Writing and Thinking*. Pitman. Answer-first structure and insight headlines.
- Revans, R. W. (1980). *Action Learning: New Techniques for Management*. Blond and Briggs.
- Kolb, D. A. (1984). *Experiential Learning: Experience as the Source of Learning and Development*. Prentice Hall.
- Gibbs, G. (1988). *Learning by Doing: A Guide to Teaching and Learning Methods*. Further Education Unit. Reflective cycle for the academic annex.
- Corporate finance textbooks for NPV, IRR and payback, further reading only: Berk and DeMarzo, *Corporate Finance*; Brealey, Myers and Allen, *Principles of Corporate Finance*.
- Client internal sources: [dataset names, owners and extraction dates].
- Related templates: `mba/mba-field-project-sow`, `mba/mba-npv-irr-card`, `mba/mba-business-communication-card`, `business/executive-summary`, `business/business-case`, `finance/investment-appraisal`.

## Revision history

<!-- Guidance: Record each version sent to the client and the faculty advisor. -->

| Version | Date | Author | Change |
|---|---|---|---|
| 0.1 | YYYY-MM-DD | [@student-1] | Storyline and exhibit list |
| 0.5 | YYYY-MM-DD | [@student-3] | Business case and sensitivity |
| 0.9 | YYYY-MM-DD | [@student-1] | Draft for sponsor review |
| 1.0 | YYYY-MM-DD | [@student-1] | Final, accepted by sponsor |

## Standard and licence note

Structure aligned with answer-first business report writing (the pyramid principle), action learning and experiential learning in management education, and standard capital budgeting (NPV, IRR, payback), which are general methods described here in original wording. This template is not affiliated with or endorsed by any business school or consulting firm and does not replace your school's course handbook or client agreement. Northfield Outdoor Co., the survey and all figures are fictional and were computed for this example. This template is original text written for this collection. It is not financial, legal or investment advice. Template licence: MIT.