Learning Module 07 · Week 7 · Individual mission
Lead a Big Data Investment Decision
Turn a technology proposal into a staged, governed investment decision.
- 1BriefingCurrent
- 2Worked exampleNext
- 3Case boardNext
- 4CheckpointsNext
- 5ReflectionNext
- 6CompleteNext
Start here
Briefing
Strategic leadership is not approval of the largest platform. It connects a clear decision to evidence, operating capability, governance, and a reversible investment path.
Use a fictional proposal. The 2026 assessment scheme and any applied capstone remain TBD, so this mission is conceptual, formative, and contains no graded deliverable or model answer. Also weigh whether people will adopt the capability and the range of outcomes it could produce.
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Game economy
Build Evidence Momentum without risking Decision XP
You begin with 3 Evidence Momentum. Any held points return when you solve that checkpoint. Evidence Momentum never falls below zero and never changes assessment marks. Complete the mission to open one transparent reward draw.
What you will practise
- Build a value chain from organisational problem to decision, capability, evidence, and outcome.LO4
- Set decision gates that test value, feasibility, risk, adoption, and accountability.LO1, LO2
6 terms for this mission
- Value hypothesis
- A testable claim about how a capability will improve a defined outcome.
- Decision gate
- A point at which evidence is reviewed before continuing, changing, or stopping a project.
- Operating model
- The roles, processes, technology, and governance used to deliver a capability.
- Benefits realisation
- The disciplined tracking of whether intended organisational value occurs.
- Technology adoption
- Whether intended users actually use a capability, which depends on its perceived usefulness and ease of use.
- Scenario simulation
- Testing a decision across many possible inputs to reveal a range of outcomes and pre-set action triggers.
Every organisation, person, figure, and dataset in this mission's scenario is invented. Real institutions, laws, and standards are named only as general context.
Sources and further reading
Every organisation, person, figure, and dataset in this mission's scenario is invented. Real institutions, laws, and standards named in this mission, including in the sources below, appear only as general context, and the sources support the concepts and methods, not the events in the scenario.
Walker, T., Davis, F., & Schwartz, T. (Eds.) (2022). Big Data in Finance: Opportunities and Challenges of Financial Digitalization (1st ed.). Palgrave Macmillan. doi:10.1007/978-3-031-12240-8
Reviews the benefits, risks and ethical costs of big-data developments across the financial sector, which is the value-versus-risk basis any big-data investment case has to weigh.
Cooper, R. G. (1990). Stage-gate systems: A new tool for managing new products. Business Horizons, 33(3), 44-54. doi:10.1016/0007-6813(90)90040-I
The original statement of the stage-gate model, in which a project passes pre-defined gates where evidence is reviewed against agreed criteria and a continue, change or stop decision is taken.
Basel Committee on Banking Supervision (2013). Principles for effective risk data aggregation and risk reporting (BCBS 239). Bank for International Settlements
Requires data capability to sit under explicit board and senior-management ownership with documented standards and independent validation, and to be considered before a new initiative is approved.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi:10.2307/249008
Defines and validates perceived usefulness and perceived ease of use as determinants of whether intended users actually adopt a technology, which underpins treating adoption as evidence a gate must review.