Many analytics projects fail to deliver the outcomes hoped for. Without the culture, resources and focus on data your analytics may fall into that trap. McKinsey highlights 7 key issues

1) Data culture must be a decision culture

• Stay true to business problems
• Focus on outcomes and business objectives
• Keep in mind the end goal

2) Data Culture, the C-Suite and Board

• The CEO must focus on beg decisions so analytics must deliver big decision making value
• You need the Board's backing on data
• All comes down to transparency and data hat adds value

3) Democratisation of data

• Stimulate demand for data at grassroots
• Embed analytics in core applications
• All personas and roles that need to make better decisions

4) Data culture and risk

• Effective data culture puts risk at the core
• If you don't have a solid foundation don't use the data

5) Culture catalysts

• Someone's got to lead the charge
• You need people who can bridge between data scientists and on-the-ground-operations

6) Sharing data beyond company walls?

• Ecosystems assume greater value delivered from assembling greater breadth of shared data
• But data leaders see data as your crown jewels
• So ensure sharing data is a valid strategic imperative for long term growth

7) Marrying talent and culture

• Need to strike balance between injecting new employees and transforming existing ones
• Take a sharp look at the skills your data team needs
• What decisions must your operational team make- what data delivers the actionable insights?

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Analytics projects usually start at the wrong point