Introduction

If age is catching up with any business input, it has to beBusiness Intelligence (BI). The ever-popular two-dimensional charts and spreadsheets littering the desks of productionheads, sales managers, procurement executives and financial chiefs are being retired quickly. They are being replaced with sophisticated dashboards, visualizations, reports and query engines. These are not new tools. They have been around, within the domain of IT specialists at very large corporations. But now, they are available to business leaders, small business owners and just about anyone keen to know industry trends, spot business problems and opportunities, improve decision making and boost operational efficiencies. One can imagine how sophisticated and pervasive BI can become when you look at how Uber, the marketplace for drivers, uses it. Uber presents real-time business intelligence to drivers with its dynamic peak-time surge pricing mechanism. By offering more take home dollars for service rendered within a small geographic area, Uber instantly attracts more taxis to the area, keeping supply and demand balanced. What better proof of the efficacy of BI than this every day example?

De-bottlenecking technology with technology

BI is changing faster than ever before. Driving this change are technology trends like Cloud, Mobility, Big Data, IoT, Artificial Intelligence and Analytics. Simultaneously, the demand for data and insights from users is growing as competition increases and regulatory requirements become more stringent (especially in industries such as BFSI, Retail and HLS). The bottleneck in keeping up with this rate of change is legacy technology.

Systems and platforms that were adopted six to seven years ago are unable to keep pace with the demand. These systems are infiexible and lack scalability; integration with other new applications and third party systems is complex; the cost of maintaining them is high; for many, end-of-life support is not available. These are signs that your BI platform is ripe for transformation.

The sooner the better

To overcome above challenges, organizations are looking for structured ways and means to standardize the governance of their BI platforms by rationalizing the existing report inventory, standardizing the BI tools across enterprise, migration to newer BI platform and then setting-up the BI governance. There is a significant cost to delaying the transformation. One study showed that organizations with low BI tool consolidation have fewer employees (~12%) using BI tools vis-a-vis organizations with high BI standardization and consolidation having more employees (~25%) using BI tools. Resultantly low BI standardization costs significantly higher on a per employee basis. The study also found that organizations that have standardized their BI tools have on average 36% lower BI spends as a percentage of revenue.

The implications of these findings go deep, suggesting that there is a hidden cost to delaying BI transformation, which many organizations fail to appreciate: in the absence of simplfication and consolidation fewer employees use BI leading to lost oppor tunities and operational inefficiencies.

BI transformation framework

The key to successful BI Transformation is to consider BI consolidation and address simplification, standardization and governance processes holistically with robust migration frameworks, tools and accelerators. The end result should be a BI platform that is fiexible, extensible and customizable.The advantages of standardization and consolidation are undeniable. To achieve this, organizations must follow four simple steps:

Tools Selection and Standardization: Work with your IT and Business Heads to understand existing and emerging BI needs. This helps choose the right technology stacks and consolidate BI into a single, world class BI platform. This has the immediate effect of improving data trustworthiness by 20 to 25% enterprise semantic models and reducing TCO by 30% owing to lowered support, maintenance and governance of fewer BI tools. Once the tools are selected, they also help define governance around them.

Report Rationalization: Multiple BI platforms result in multitude of reports residing within the organizations without any systems to keep tab on their usefulness. Organizations need to document their inventory of reports with a structured and automated process for identification of similar/duplicate and 鈥淯nused/Unuseful鈥� reports and their rationalization. Typically, 40-50% of reports are found to be candidates for rationalization and their elimination can bring down generation and maintenance costs by upto 25%1.

Platform Transformation: Users are accustomed to set patterns, processes and dashboards. How will they respond to change? There are two aspects to Platform Transformation: technology migration and change management from a user perspective. It is best to define a framework for migration that includes automation to reduce time-to-market and ensure low error rates. Extracting metadata from existing systems and mapping it to the target platform is crucial. You should be able to transform data from your system to any target system of choice. It is also recommended that change management processes be put in early by explaining the technical benefits to users, creating awareness of the simplification and reducing user discomfort.

Governance & Roadmap Definition:A sound BI Transformation Plan includes governance (policies and processes) and a roadmap. These need to be aligned with users, organizational process maturity and technology adoption. For example, On-premise, Cloud and Hybrid models will demand different governance processes, depending on industry/regulatory requirements and technology environments. The value of good governance cannot be underestimated. Many organizations show 20% more benefit realization when they have good governance in place.

Time to make the move

To gain the advantages of new technology, organizations are getting ready to undertake a BI Transformation journey. This is because organizations are moving from historical reporting to planning and forecasting in a bid to identify and address emerging opportunities.Unless efforts and investments towards standardization and consolidation rise up the priority charts of organizations, organizations will continue to be exposed to risks of underachievement on the critical strategic agenda of Business Intelligence.

Deepak Maheshwari听is a Business Intelligence enthusiast with almost 17 years of experience in helping customers in identifying, consulting and solving underlying 鈥渄ecision management鈥� problems.In his current role, he heads the Enterprise Business Intelligence practice within 91快活林 and is responsible for managing practice growth. He is one of the key thought leader who helped conceptualize BI Transformation and has architected multiple solutions under it, not only helping customer to understand the risk of their BI landscape standardization and consolidation but also standardized the whole migration process through some well defined frameworks and automated tools.

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