MBA Field Project Report Template

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.

Document control

Approvals

Contents

• 1. Executive summary
• 2. Key question and scope
• 3. Situation
• 4. Approach
• 5. Findings
• 6. Options considered
• 7. Recommendations and business case
• 8. Implementation roadmap
• 9. Client sign-off and handover
• 10. Team reflection (academic annex)
• 11. Quality checklist and common mistakes
• 12. Appendix: data, assumptions and calculations
• Sources and further reading
• Revision history
• Standard and licence note

1. Executive summary

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

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

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)

4. Approach

Hypothesis results:

5. Findings

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)

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.

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 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)

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

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

7.1 Recommendations

7.2 Economics

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

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)

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

8. Implementation roadmap

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

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.

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)

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

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

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

Assumptions log

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

• 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

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.