CMI Unit 709 Strategic Management of Data and Information (R/617/6869) Assignment Brief 2026

CMI Unit 709 Assignment Brief

Assignment Aim

The aims of this unit are for leaders to see strategic management of data and information as an opportunity rather than a challenge.  Leaders will understand the strategic value and use of data and information and will critique strategies for its effective management. The unit culminates in the opportunity to develop a strategy to improve the use of data and information in a strategic organisational context.

Learning Outcomes and Assessment Criteria

LO1 – Understand the strategic management of data and information

Assessment criteria

1.1 Critically discuss the strategic use and value of data and information

1.2 Critically appraise the challenges of managing data and information in an organisational context

1.3 Evaluate approaches to the effective strategic management of data and information

1.4 Recommend a strategy to improve the management of data and information in an organisational context

Indicative content

1.1 Strategic use of data and information: Generic roles/emerging capabilities which use data and information: Data science, informatics, business analysis, business intelligence/data visualisation. Emerging developments (for example, machine learning, Artificial Intelligence, real time decision making, automation, data orchestration).

Strategic value of data and information: Enterprise asset. Financial value. Competitive advantage.

Development of people and/or organisational capabilities. Contribution to decision making at operational and strategic levels (for example, HRM/HRD. Operations. Finance. Procurement. Logistics. Product development. Marketing, Service delivery). Influence on project and programme management, innovation and change management, leadership strategy. Value and use to organisations in specific contexts (for example, Public, private, third sector, local national international, global organisations including legal status and levels of organisational maturity).

Data and information: (for example, Internal and external data and information in public and private domains). Use of qualitative and quantitative data and information. Text, images, numbers, multimedia, structured, unstructured, count, measurement, metrics and attribute data).

1.2 Challenges:

• Approaches to how data and information is acquired, created, stored, used, shared and managed (for example, use of enterprise, process, data architectures).
• Capability of technology to support the management of data and information (for example, legacy systems, cloud solutions (for example, AWS – Amazon Web Services)). Capability of strategic data and information management to respond to change (for example, organisational growth, merger, compliance, consolidation).
• Financial cost to acquiring, developing, maintaining and managing data and information (for example, Cost of ICT i.e. licence fees, people development).
• Risk (for example, data breaches, cyber security, Intellectual property, reputational risks, litigation, insourcing/out scouring data and information, data security, backup, hardware/software risks).
• Current and future capabilities: levels of knowledge, skills, expertise and leadership styles (for example, Hay/McBer). Behavioural competences (Boyatzis, 1982). Future Competences (Morgan, 1985). Technical skill development i.e. business analysis, programming, project management (for example, Prince 2, APM, PMI, Gantt charts, spreadsheets, simple data bases). Ability of people to interpret, select and weigh evidence, draw conclusions (for example, currency, validity/relevancy, authenticity, and sufficiency). Organisational and information cultures (for example, sharing, participating).
• The ability to use Systems Thinking: for example, Soft Systems Method (Checkland, 1980). Viable Systems Model for organisation design (Beer, 1970). Critical Systems Heuristics (Ulrich, 1990). Strategic Options Design and Analysis (Eden et al., 1990). Strategic Assumption Surfacing and Testing (Rosenhead et al., 1990). Critical Systems Thinking (Jackson, 2019).
• Legal and regulatory frameworks. National/international (for example, Data Protection Act,

2018, GDPR, 2018. Freedom of Information Act, 2000. IS0/IEC 27000 Information security. ISO/IEC 20000 Service management. ITIL. Cobit 5). Protocols for accessing and sharing data (cross functional data requirements). Ethical practice.

1.3 Strategies for the effective strategic management of data and information: Approaches to data acquisition, storage, creation, usage, management, sharing (for example, use of enterprise architectures i.e. Zachmann, eTOM, TOGAF). Process and data architectures (for example, metadata models). Development of new ICT capabilities. Development of ‘Legacy’ systems. Use of Systems Development Life Cycles (for example, Agile/RAD, SRUM, Waterfall and “V” model). Purchase of COTS packages (for example, Enterprise

Resource Planning (ERP). Materials resource planning (MRP). Application of current and emerging

technologies for specific organisational contexts (for example, Simple and Smart invoicing, cashless transactions). EDI (Electronic Data Interchange standards and protocols). Spreadsheets and software for specific business functions. Business to business and business to consumer technologies. VANs (Value Added Networks). Peer to peer technologies. Internet and intranets. Blockchains. Cloud technologies.

Cybersecurity. Data base types (for example, use of Relational, Hierarchical, Object, Graph, Network,

Pointer). Technologies for Data Mining, Data Visualisation. Dealing with “Big Data”. Industry 4.0, Industry Convergence and FinTech. Disaster recovery, business continuity strategy, problem and service management (ITIL). Crisis management planning.

1.4 Strategy to improve the management of data and information: Approaches to the way data is acquired, created, stored, used, managed, shared. Data governance (policies and procedures). Stewardship and ownership. Approaches to collecting/selecting/rationalising data volumes and quality (clean data). Use of people analytics and metrics. Data Science and Informatics. Rationalisation of data formats and data definitions, data sets, data bases, technologies, applications, for example,, use of spreadsheets and COTs packages. Approaches tailored to strategic requirements, decision making (for example, Reducing process waste and variation – Lean and Six Sigma. Financial and cost analysis. Market segmentation. Customer behaviours and analytics. Product and Service costing and pricing. Purchasing and procurement decisions). Benchmarking (for example, use of PIMS – Profit Impact of Market Strategy, EFQM Excellence Model, Baldridge Model).

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