Data Management Strategy

• Organisations up the maturity curve (descriptive -> diagnostic -> predictive -> prescriptive analytics)
• Improved data quality / security
• Common understanding of the meaning of data
• Better trained staff
• Simplified, cost-effective data management
• More effective data architecture
• Enhanced understanding of existing and available data
• Knowing what you’ve got and where it is
• Assured compliance with regulations
• Clarify / establish what constitutes a single view of the truth
• Improved capability to deliver
• Established clear data ownership and buy-in
• Faster access to reliable data
• Reduced technology complexity / obsolete systems removed

• Reduction in data silos / information silos
• Avoid data creep (don’t copy data from application to application)
• Reduced time wasted looking for data
• Avoid data duplication / multiple versions and associated costs
• Means (and confidence) to remove out-of-retention data (and clean start)
• Avoid conflicting / confused reporting
• Avoid fines / unnecessary costs
• Instil effective and sustainable information governance
• Reduced repetition of errors / use of old processes
• Reduced friction between data sharing departments

Data Management Strategy is defined for an organisation when the top level management realises the importance of having one in place to up the organisational data maturity, provide compliance assurance, understand the value of their data (possibly monetise it too) and make data available for anyone who needs it easily in a secure way.

The first step is to understand the As-Is state of all the data in play – what it is, where it is, who is reponsible for it, how is it maintained etc.

Formulate the strategy by identifying the capabilities needed to be in place for this to work – Data Governance, Master Data Management, Data Quality, Data Security, Data Privacy to name a few.

The time it takes to deliver the strategy document depends on the size of the task / organisation / data in play. In a typical organisation, you can come up with a high level strategy in a couple of months.

Formulate a data management strategy that achieves the overall business goals, reduces costs / operational friction / time to market, improves data quality / security / privacy / staff productivity / predictability / time to market / value of the data and provide data accessibility to the right people at all times easily in a secure manner.

A comprehensive Data Management Strategy document that covers all aspects of data management.

Project based engagements operate on the basis of agreeing work and any outcomes or milestones for delivery in advance of commencement of any engagement in a ‘Statement of Work’. Prices are fixed for the agreed deliverables and should changes be required, these may incur changes to delivery costs. Payment for Project Based Engagements are agreed on a case-by-case basis, giving consideration to risk, contract value, client payment history, relationship longevity and duration.

• Data Management
• Data Governance
• Data Architecture
• Data Strategy
• Data Quality

• Digital Enablement

• Banking and Capital Markets
• Financial Services
• Insurance
• Media and Entertainment
• Pharmaceutical and Life Sciences

• Data, Information & Security Management
• Strategy, Innovation and Business Design