“There are many methods for predicting the future. For example, you can read horoscopes, tea leaves, tarot cards, or crystal balls. Collectively, these methods are known as “nutty methods.” Or you can put well-researched facts into sophisticated computer models, more commonly referred to as “a complete waste of time.”
Are you clear on your objective? What is the most important value proposition that you want to achieve through BI and analytics enabled strategies?
- Reduction in operating expenses
- Increased profitability
- Improve growth, competitiveness and market position
- Customer acquisition, loyalty and retention
- Product development and differentiation
The misalignment between what the C-suite wants and what IT is capable of delivering is quite extraordinary. Many CFOs and CEOs believe that IT is unable to deliver results where it counts: the top line and bottom line. At the same time, IT organizations spend an incredible amount of time, money and resources simply reporting the obvious data within their business processes and workflows. The data overload is making finding the obvious in the increasing tidal wave of structured and unstructured data a full-time job. As organizations emerge from the deep recession of 2008, the competitive pressures are putting even greater demands on the decision-making, KPIs and performance management processes of organizations.
To stay competitive means making better decisions more quickly. It means accelerating the “raw data -> clean data -> information -> insight -> decision cycle.”
It dictates widening the scope and scale of the data management domain, the analytic landscape and the technological infrastructure.
Is it fair to associate the reports, dashboards of the obvious with the notion of business intelligence (BI)? The short answer is yes and no. The 21st century Instant Age – with its 24×7 customer interaction, global supply chains, increasingly digital/mobile/social/collaborative business processes – will need a BI overhaul and reconfiguration.
BI is more than basic or sophisticated reporting. It is about actionable insight, supporting better decision-making by identifying business opportunity or challenge and adapting to business change. Being able to execute practice BI requires architects (both IT and Business) to go well beyond merely reporting the obvious data about business operations. Simply put, leveraging the sophisticated dashboard technology is a means to an end…not the end itself.
Building BI systems to support better decision making requires business and IT architects to answer two questions:
1. What is the decision-making process? There exists a mature body of knowledge about decision support, Key Performance Indicators and performance management (finance, supply chain, sales). The notion of helping organizations make better decisions and become more efficient is hardly new. To effectively implement systems that support the decision-making process of different user communities requires that you hire the right subject matter experts and understand the decision support subject area.
2. How can the BI implementation make that process better? Once the BI architect has a grasp of decision-making processes, it is important that he/she answer two subordinate questions:
- What decision-making patterns are recurring, repeatable and supportable? What levels need what information to effectively monitor and control activities and all related performance?
- What technologies and architecture are necessary to support those decision-making patterns? Is there need for a “single source of truth” or a federated model possible?
The point we are trying to make is that more sophistication is needed in the business driven front-end of the BI projects and not fall into the trap of being technology led (or vendor platform choice led). This sounds basic but we are seeing this pattern again and again.
Our meetings with clients are showing us a clear trend — Data Management, BI and Analytics are priority topics that executives want to get a handle on. It is clear that there is a huge avalanche of demand building on the business side. But paradoxically, we are also seeing that data management and BI platform budgets are severely constrained. Why?
As we pull out of the economic downturn, the future of BI depends on altering the approach and mindset to address the burning questions CEOs care about most. We have to challenge an entire data management industry to change their role from tactical implementers of traditional BI projects to strategic coordinators of organization-wide, transformational data initiatives aimed at profitably delivering value to sales teams, supply chain leaders, and customers. Different times call for different leadership skills.
Shirish is EVP Business Analytics Solutions at Saama Technologies, where he focuses on building business-specific analytics solutions. Ravi Kalakota is Managing Director at Alvarez & Marsal, a restructuring, turnaournd, performance improvement, and business consulting firm.
This blog post was originally published at Business Analytics 3.0.