MOD007666 Entrepreneurial Action Report

MOD007666 Entrepreneurial Action helps you turn a simple idea into something real that solves a clear problem. You learn how to spot opportunities, speak to potential users, and test your assumptions with quick, low-cost experiments. The module keeps things practical: you build a value proposition, outline a lean plan, and decide the smallest next step that proves whether the idea is worth more time and money.

Across the term you create a basic prototype or service outline, track simple metrics (such as sign-ups or enquiries), and reflect on what worked and what did not. You also cover key issues like budgeting, risk, legal basics, and ethics, so your idea is not only desirable but also feasible and responsible.

By the end, you can present a short pitch with evidence from your tests, a clear action plan, and options for growth. The focus is on real-world learning, making decisions, adapting quickly, and communicating your results with confidence.

Sample of MOD007666 Entrepreneurial Action

Executive summary

This action-research project develops an entrepreneurial proposition for a mid-sized UK convenience retailer (“NorthStar Convenience Ltd”, a realistic composite organisation). The proposition is to design and pilot smart click-and-collect lockers at store exteriors to (1) capture online impulse and top-up missions, (2) extend trading hours for collection beyond staff shifts, and (3) lower last-mile costs. The project is conducted exclusively with secondary sources (industry reports, company disclosures, trade press, academic literature). No interviews, surveys, or observation were undertaken.

The report: (a) justifies the market opportunity; (b) synthesises relevant literature on entrepreneurial opportunity, business model design and diffusion; (c) specifies a desk-research methodology; (d) analyses feasibility, economics, and risks; and (e) provides a phased implementation plan with measurable outcomes. Conclusions recommend a two-store, twelve-week pilot with pre-defined success metrics and a roadmap to scale. Post-module, primary research (e.g., shopper intercepts, usability testing) is suggested as future work.

1. Entrepreneurial opportunity (10 marks)

1.1 Problem and opportunity

UK convenience shoppers seek speed, certainty, and safe pickup options. Many independents and symbol-group stores struggle to offer reliable home delivery at sustainable cost; locker-based click-and-collect converts online orders into low-touch pickup with predictable cost per order, reduced queueing, and extended pickup windows (e.g., 06:00–23:00). For the organisation, lockers may grow online basket penetration, lift attachment sales in-store when customers pick up, and provide operational smoothing (batch picking).

1.2 Value to the community of practice

• Customers: time-saving, reliable pickup, after-work flexibility.

• Store teams: fewer time-critical deliveries, fewer queue spikes.

• Management: clearer last-mile unit economics; data on demand patterns.

• Local residents: reduced delivery vans and short-stopping on narrow streets.

1.3 Objectives and scope (SMART)

1. Design a locker-enabled click-and-collect flow for small-box grocery within 4 weeks (desk research only).

2. Plan a two-store pilot (urban/suburban) with a target of 25 orders/week/store by week 8 of pilot.

3. Achieve an on-time pickup rate ≥ 95% and order accuracy ≥ 98% during pilot.

4. Evidence unit economics to breakeven at ≥ 18 orders/day across the two stores (model assumptions from secondary sources).

5. Document a scale-up blueprint within 12 weeks.

1.4 Business model context

Using the Business Model Canvas:

• Proposition: fast, reliable, out-of-hours pickup of top-up grocery orders.

• Segments: time-pressed local shoppers; shift workers; parents on school runs.

• Channels: store app/website; local search; QR at storefront.

• Revenue: item margin + modest convenience fee; supplier co-funded promos.

• Key activities: online assortment, batch picking, locker loading, exception handling.

• Key resources: lockers, order management system, staff picking time.

• Costs: locker rental/lease, integrations, maintenance, packing materials (minimal).

• Partners: locker vendor, payments, e-commerce platform, last-mile courier (for returns).

Only secondary evidence is used to justify feasibility and benchmarks.

2. Research methodology (10 marks)

2.1 Approach

An action-research logic is followed but, in line with module rules, all evidence is secondary: academic literature, UK retail trade bodies, company case studies, analyst notes, and government publications. The “action” here is the design of a pilot plan grounded in secondary evidence and reflective learning.

2.2 Search strategy and selection

• Databases/collections: university library (business/management), Google Scholar, publisher databases, UK Government/Open Data, trade associations.

• Inclusion: UK or comparable retail contexts; last-mile, BOPIS/Click-and-Collect, grocery e-commerce, small-format operations; literature on opportunity recognition, diffusion, effectuation, and business model design.

• Exclusion: primary data studies requiring human participation; non-credible blogs; non-UK regulation unless generalisable.

2.3 Data extraction and analysis

• Literature mapping to themes: demand drivers, locker economics, customer adoption, operational fit, risk.

• Comparative synthesis of reported metrics (e.g., collection uptake, NPS proxies).

• Light financial modelling using published cost ranges and public vendor pricing where available.

• Quality appraisal (source credibility, recency, transferability).

2.4 Ethics (PASS/FAIL requirement)

Secondary research only. No personal data processed. Copyright respected via proper citation. An Ethics Stage-1 form is completed; online quiz screenshot appended. Any screenshots/figures used in internal study packs would be either created by the student or used under permissible licences.

2.5 Limitations

No direct shopper testing during the module; transferability from case studies may vary; vendor pricing can be opaque; small-store constraints (power, pavement width) differ by site.