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
