Business Intelligence Strategy and Big Data Analytics
Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts – people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others.
“If you need to think about BI (and all the related topics) strategically in your company, I’m confident that you will find this book to be very helpful.”
The Profit Impact of Business Intelligence
The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company’s data assets or data warehouse.
BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver.
“The ideas in The Profit Impact of Business Intelligence were central to our deployment of business intelligence applications that allowed us to manage revenue delivery and reduce costs.”
“One performance management approach we are taking is to leverage business intelligence to better serve our customers and to optimize our cost structure in relation to the services our customers value most. We have used the strategies described in The Profit Impact of Business Intelligence to align our BI program with our critical success factors and to drive our BI development efforts.”
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While we are the leader in our market, we operate in an increasingly competitive environment, and one performance management approach we are taking is to leverage business intelligence to better serve our customers and to optimize our cost structure in relation to the services our customers value most. We have used the BI Pathway Method to align our BI program with our critical success factors and to drive our BI development efforts.
Thanks for all the work to date and the valuable perspective, especially the willingness to challenge our approaches on a number of fronts; exactly the type of push we benefit from.
From our book
The Human Face of BI and Analytics
Developing a BI Strategy using the methods we describe our book allows us to “get into the heads” of key executives and managers to find out what analytics they need to enhance business results. How do they see their world, what are they looking to accomplish, and how do they want BI, analytics, and AI to help them? And what do they think about ideas we offer based on our experience? We can build a business case that is “bullet-proof” from a logical, corporate perspective, but it also has to resonate with business people on a more intuitive level that squares with what they believe they would be able to do achieve if they had better BI, analytics, and AI. After all, it is business executives who ultimately decide to fund BI, so let’s put a human face on it.
BI in the Era of Big Data and Cognitive Business
Business executives, managers and analysts have wrestled for over two decades with the problem of understanding how to leverage data to improve business results. For much of that time, the umbrella term “business intelligence”—or “BI” for short—has been used to describe a family of business analysis techniques ranging from standard reports to highly sophisticated advanced statistics. More recently, terms like “big data” and “analytics” have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness.
The Strategic Importance of Business Intelligence
The power of BI in terms of production has become increasingly clear over the years, and there is no debate that it plays a key role in achieving competitive advantage. At the same time, one must consider industry, company, business model and competitor’s actions when determining the strategic importance of BI. Generally, the more complex and information-intensive an industry is, the greater the strategic importance of BI and the greater the opportunity for competitive differentiation. Through understanding the strategic importance of BI in the context of industry and business model, a clear BI mission and strategy can be formed. These considerations affect the pace of capital investment, funding for the BI program, pace of resource acquisition and/or utilization, pace of BI deployment and ultimately the pace and magnitude of business value creation.
BI Opportunity Analysis
To succeed in leveraging business intelligence (BI), it is critical to move beyond vague and/or generic value propositions. Purported benefits such as “enabling better decisions,” “increasing customer intimacy” and “enhancing supply chain agility” are, for the most part, insufficient in convincing executives to invest in BI. Executives want to know precisely how BI will benefit the company. How do proposed investments in BI relate to enterprise and/or functional business strategies? Which business processes will be improved and by what type of BI? What economic return can be expected over what general timeframe? Accordingly, to obtain funding and shape an affective BI program, it is necessary to identify, define and document BI opportunities, or BIOs for short. BIOs provide the investment hypotheses, value propositions, and/or business cases for investing in BI to improve profitability. The process of identifying BIOs is called BI Opportunity Analysis, and there are a number of techniques that can be used.
Prioritizing Business Intelligence Opportunities
Most companies are able to identify multiple business intelligence opportunities (BIOs)—opportunities to leverage BI to increase revenues, reduce costs, or both. Realization of these BIOs requires a joint effort between business sponsors, business subject matter experts, and the technical teams who execute BI projects. Given finite resources, the identified BIOs need to be prioritized for execution over time—typically via a series of rapidly executed projects over the course of a few years. There are a number of factors that can be considered when prioritizing BIOs, and different companies employ differing degrees of formalization in doing so. For some companies, structured conversations about the BIOs are sufficient for agreeing on the priorities. For others, more rigorous multiattribute scoring techniques are favored. And of course many companies require some form of return-on-investment (ROI) analysis.
Leveraging BI for Performance Management, Process Improvement, and Decision Support
Business intelligence (BI) is ultimately about improving business performance. The primary way that BI can increase revenues, reduce costs or both is by improving the business processes that drive those results. Improvements can be in the form of enhanced process efficiency and effectiveness, and/or more effective, streamlined, and automated decision support. The most relevant business processes to target for improvement generally fall into three broad categories: 1) performance management processes; 2) revenue generating processes; and 3) operating processes. Performance management processes include planning, budgeting, performance monitoring, variance analysis, scenario analysis, and economic forecasting/modeling. Revenue generating processes include marketing, sales, produce development, product management, and customer service. Operating processes include purchasing, manufacturing, logistics, demand forecasting, sales and operating planning, order management, human resources development, asset management.