When it Comes to Important Business Decisions, Should You Trust Your Gut or Follow the Numbers?
Deloitte Debates
Many leadership teams rely mainly on their collective wisdom to drive smart business decisions. Others claim they can achieve more reliable outcomes by primarily using data-driven, science-based predictive analytics. Who’s on the right path?
Here are some thoughts about the future of BI and DSS :
“Only Paranoid Survive”, today’s hyper competitive, globalized economic environment push forward-thinking organization to framework the BI infrastructure, embedded analytics into corporation culture, streamline the decision management scenario, reinvent the capability enabled, decision driven enterprise.
There are many BI and analytics applications with all flavors in the market: from descriptive analytics, diagnostic analytics, predictive analytics, to prescriptive analytics, from operational BI , Artificial BI to Social BI, today’s BI solution helps organization overview what happened via historic operational data, quite often a bit outdated , or use customer survey data to predict and optimize the marketing campaign result, though,sometimes those sample data may not completely reflect customer’s point of view.
Today’s BI solution make some milestones, but not perfect yet: many BI projects didn’t bring up the expected result or failed to deliver the ROI due to variety of limitation: poor data management, overly complicated interface, silo divisional solution, BI is just at the turning point: should BI keep as the different breed of animal, or it could be unified into more integrated solution with better customer satisfaction, if so, what should it look like:
· Outside-in Point of View: today’s BI KPI scoreboard deliver the inside-out perspective, the next generation of BI will directly catch customer and partner’s data via multiple channels, to build up the customer-centric organization, the EDW (enterprise data warehouse) should have the capability to process the full-set of customer data (Big Data), with more advanced information management system such as MDM, data quality and data integration.
· Self-Service User Interface: many of today’s BI users are data analysts, BI technician, the future of BI should have broader base of self-service users, from executive to front-line employees, the feasible BI tools could become one of the hottest enterprise soft gadgets, search-based, self-service, with persona oriented KPI scoreboard or dashboard, help make the real-time decision from each level.
· Deliver the Foresight view: Today’s BI intent to catch some insight, the next generation of BI focus on percepting the future, what will be happening, so the organization could well prepare their next step regarding the product or solution development, customer service optimization, new business model creation., etc.
· Optimize Decision Making Process: the organization with higher level of BI maturity have the advanced analytics embedded into corporation’s DNA, centralized BI infrastructures, it has better integrated decision making process framework and scenario planning.
The next generation of BI may not only have the full-fledged BI capabilities (BI+PA+SI+AI.,etc), it could be more agile, cost-effective, and easy to use, with the right scale and scope, help make the right decision at the right time at every level, to reinvent the instant-on, intelligent organization
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