Analysis of stop searching for that elusive data scientist by michael schrage
- 1. Analysis of Stop Searching for That Elusive Data Scientist by Michael Schrage By Darpanraj Deoghare
- 2. What do we read in the paper Surveys say there simply aren’t enough people with the unusual blend of software skills and statistical savvy to go around. For many organizations, a mediocre data scientist may be worse than none at all.
- 3. Big organizations can afford — or think they can afford — to throw money at the problem by hiring laid- off Wall Street quants or hiring big-budget analytics boutiques. More frugal and prudent enterprises seem to be taking alternate approaches.
- 4. Insights
- 5. Insight – No.1 The concurrent rise in Big Data and analytic opportunities means that smart organizations would be foolish to outsource this away from the very people who need to be more data- driven.
- 6. Insight – No 2 Stop hunting for that data science unicorn and/or silver bullet. Chances are slim that your organization would even be able take full advantage of their talent.
- 7. Insight – No 3 Empowering small cross- functional data- oriented teams • The teams must be explicitly charged with delivering tangible and measurable data- driven benefits in relatively short periods of time. • The emphasis is on building greater data capability than better digital infrastructures.
- 8. Relevance
- 9. Relevance for Managers Better Collection Understanding of the Employees o Better the opportunities to the team. o Better Relations between the staff. o Better learned the workforce will be
- 10. COST-SAVING FOR A COMPANY • Big savings deal for the company by investing in small teams, rather than hiring the savvy quants. • Limited ambition could do a better job attracting credibility and support than BHAGs.(Big Hairy Audacious Goal)
- 11. Relevance for Managers Managers need to consider all possible metrics to lead a successful organisation. Managers need to critically think all metrics without ignoring the stubborn facts of fewer metrics which efficiently help in preventing the downfall of the organisation.
- 12. Conclusion People don’t need to become data scientists, but they do need to understand and appreciate key principles and practices of data science. The temporary fix of data science teaming doesn’t solve the problem, but it creates the cultural and organizational context for the necessary hires to follow.
- 13. Submitted for Internship "Data Analytics " under Professor Sameer Mathur , IIML By, Darpanraj Deoghare
- 14. Summary – Contd. This is only the first step, but a critical one if we are to derive sustainable advantage from data, big and small.
- 15. Thank You