Making advanced analytics work for you
- 1. Making Advanced Analytics Work for You Making Advanced Analytics Work for You
- 2. • Big data and analytics have rocketed to the top of the corporate agenda. • Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data.
- 3. • They also see that big data is attracting serious investment from technology leaders such as IBM and Hewlett-Packard. • Meanwhile, the tide of private-equity and venture-capital investments in big data continues to swell. .
- 4. • The trend is generating plenty of hype, but we believe that senior leaders are right to pay attention. • Big data could transform the way companies do business, delivering the kind of performance gains last seen in the 1990s, when organizations redesigned their core processes. • As data-driven strategies take hold, they will become an increasingly important point of competitive differentiation
- 6. • Experts descended on boardrooms promising impressive results if new IT systems were built to collect massive amounts of customer data. • To be fair, most companies eventually managed to get their CRM programs on track, but not before some had suffered sizable losses and several CRM champions had lost career momentum
- 7. • Given this history, we empathize with executives who are cautious about big data. Nevertheless, we believe that the time has come to define a pragmatic approach to big data and advanced analytics—one tightly focused on how to use the data to make better decisions. • Two important features underpin those activities: a clear strategy for how to use data and analytics to compete, and deployment of the right technology architecture and capabilities.
- 8. CHOOSE THE RIGHT ONE
- 9. • The universe of data and modeling has changed vastly over the past few years. The sheer volume of information, particularly from new sources such as social media and machine sensors, is growing rapidly. • The opportunity to expand insights by combining data is also accelerating, as more- powerful, less costly software abounds and information can be accessed from almost anywhere at any time.
- 10. GET THE NECESSARY IT
- 11. • Legacy IT structures may hinder new types of data sourcing, storage, and analysis. Build Models That Predict and Optimize Business Outcomes . • Data are essential, but performance improvements and competitive advantage arise from analytics models that allow managers to predict and optimize outcomes.
- 12. Build Models That Predict and Optimize Business Outcomes
- 13. • Data are essential, but performance improvements and competitive advantage arise from analytics models that allow managers to predict and optimize outcomes. • More important, the most effective approach to building a model rarely starts with the data.
- 15. • The lead concern expressed to us by senior executives is that their managers don’t understand or trust big data–based models. • Develop business-relevant analytics that can be put to use. • Like early CRM misadventures, many initial implementations of big data and analytics fail simply because they aren’t in sync with the company’s day- to- day processes and decision-making norms.
- 17. Managers also need to get creative about the potential of external and new sources of data. Social media are generating terabytes of non- traditional, unstructured data in the form of conversations, photos, and video. Add to that the streams of data flowing in from sensors, monitoring processes, and external sources that range from local demographics to weather forecasts