Introducing the APO Thought Leader Series
Introducing the APO Thought Leader Series
As an ongoing part of this blog, I wanted to bring in some third parties with deep technical and industry experience as contributors to a Thought Leader Series. The first expert I wanted to introduce is David Loshin.
David Loshin, president of Knowledge Integrity, Inc, (www.knowledge-integrity.com), is a recognized thought leader and expert consultant in the areas of data governance, data quality methods, tools, and techniques, master data management, and business intelligence. David is a prolific author regarding BI best practices, via the expert channel at www.b-eye-network.com and numerous books and papers on BI and data quality.
For a good introduction to business intelligence, consider reading David’s book, “Business Intelligence: The Savvy Manager’s Guide.” This book has been hailed by
prominent data warehousing and business intelligence educators as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing, and how all of the pieces work together.”
His book, “Master Data Management,” has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at www.mdmbook.com. David can be reached at loshin@knowledge-integrity.com, or by phone at (301) 754-6350.
Here is the first installment of this series from David:
Business Intelligence Fundamentals – Driving Organizational Improvement
An oft-quoted statement states that one cannot improve that which is not measured. And when we look around our organizations, there are always opportunities for improvements. But an effective outlook for any type of improvement involves some critical concepts to be internalized within any organization striving for self-betterment, including:
1. Measurement and assessment, as a way of prospecting for areas for improvement;
2. Evaluation and prioritization, to identify opportunities;
3. Developing an action plan, intended to adapt processes that can improve the business;
4. Defining success criteria that indicate when the business objectives have been met;
5. Implementing the plan so that the improvements can take hold; and
6. Measuring results against the success criteria.
Gaining visibility and insight into ways to improve our processes is always a good thing, and therefore it is should not be difficult to justify the need for tools and techniques that provide this kind of insight. For the past few years, this is what business intelligence (BI) is all about: a common set of tools, techniques, and procedures used to organize, analyze, and report on strategic performance. It turns out that the value is not limited to strategic activities – any type of business process can be improved when informed by the ability to define metrics, measure, and report on those metrics using the tools and techniques provided by a business intelligence capability.
But business intelligence may begin with organizing data for reporting and analysis, then take you much further than that. The initial approach to reporting provides a review of what has already happened as a way to determine how well your decisions matched the business need. But different, more sophisticated types of analytical applications can build upon the basic organization of information to actively advise individuals in various roles across an organization:
· At the organizational level (such as sales compensation planning, financial consolidations, category analysis, marketing directives),
· At the team-oriented decision making level (collaboration, centrally shared data, workflows, quick and secure analysis and sharing of information), and
· At the personal decision making processes that inform our daily jobs (such as which of the new customer leads are the most likely to purchase, or how many customers of a specific product within a territory are likely to purchase again).
If all of this is true, then why do so many organizations experience challenges in justifying, funding, planning, and executing a business intelligence strategy? What have been the traditional roadblocks to BI success? How can one evaluate the need for BI and execute against that need? And what types of tools, techniques, and best practices support BI?
The objective of this blog is to explore these, and many other questions, to help readers understand the value of business intelligence, explore the issues in realizing that value, and look at ways to make BI work in the organization. Over the coming months, we will look at issues such as:
· Assessing BI requirements and expectations
· Establishing a value proposition for BI
· Data warehousing and business intelligence
· Data quality
· Performance indicators
· What is “data mining”?
· Data governance and controlling “data spread”
· Predictive analytics vs. common sense
· And many others
We will establish fundamentals and build on that foundation to understanding how to assess the value of business intelligence and selectively introduce those concepts into the organization. Of course, reader input is critical, and hopefully your comments and questions will contribute to the discussion. There are many opportunities for benefitting from business intelligence, and I am looking forward to exchanging ideas that can help “democratize” BI and bring these ideas down from the ivory tower and put them on anyone’s desktop.