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?
Read the full article link below and also see:-
Analytics projects usually start at the wrong point
For leading and lagging companies alike, the emergence of data analytics as an omnipresent reality of modern organizational life means that a healthy data culture is becoming increasingly important. With that in mind, we’ve spent the past few months talking with analytics leaders at companies from a wide range of industries and geographies, drilling down on the organizing principles, motivations, and approaches that undergird their data efforts. We’re struck by themes that recur over and again, including the benefits of data, and the risks; the skepticism from employees before they buy in, and the excitement once they do; the need for flexibility, and the insistence on common frameworks and tools. And, especially: the competitive advantage unleashed by a culture that brings data talent, tools, and decision making together.
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