Practical Business Intelligence

Introduction

The goal of Business Intelligence (or “BI”) should be to assist business in maximizing the value of their data.  Whether companies know it or not, their data is one of their most valuable assets for strategic and operational decision-making.  When done right, BI has the potential to deliver highly relevant, highly targeted applications, reports, and dashboards, designed to maximize an organization’s ability to gain specific, actionable knowledge from their corporate data. That means valuable tools like statistical analysis and predictive analytics, and cross-referencing data from different departments to mine for trends. Valuable stuff!  When done wrong, BI has the power to create organizational, political and technical debacles of Biblical proportions.  Not good.

So, how do you navigate the minefield of complex topics like Business Intelligence?  What about important supporting topics like data warehousing, data governance, data stewardship, etc?  How do you make sure that the decisions your organization is making are the best possible ones – data driven, insightful, and packed with value for your business?

In this edition, we’ll take a slightly different approach in discussing BI best practices.  Let’s talk about a few of the things you really shouldn’t do, if you want your Business Intelligence initiative to succeed.

Bad Idea #1:  Pick the Technology First

Myth: The technology is the hard part

Many see Business Intelligence or Data Warehousing as technology problems.  They get budget and approval, do lots of research, have vendors give demos and promise endless mentoring … all in the industrious (if misguided) attempt to “buy” Business Intelligence.

Unfortunately, BI is not, and likely won’t be soon, a technology platform.  It doesn’t come shrink-wrapped … at any price.  It can’t be bought from anybody like you’d buy a copy of Windows from Best Buy.  BI is a new way of thinking, best practices molded by nearly two decades of successes and failures, architectural paradigms for data and software, changes to your organization, overcoming political hurdles, and much more.  The truth is that the technology is actually the (comparatively) easy part.

Here are some hurdles I’d recommend overcoming before you even talk about the technology you’ll use to undergird your efforts…

• Securing executive commitment (including funding)
• Building consensus among business functions (and conforming data dimensions)
• Establishing effective data and IT governance
• Developing a change control management plan to control scope and growth
• Accurately defining requirements
• Figuring out how the system will be supported after it’s built
• Etc, etc, etc

So, let me suggest that there is an order of priority to focus on when launching a BI initiative or project:

1. The Plan – What exactly are you trying to accomplish, and how does it support the organization’s KPI’s?
2. The People – Who is going to accomplish your plan?  What roles will they play?
3. The Process – How will this awesome plan be accomplished?
4. The Technology – Now that you have all this in place, let’s talk about what tech you’ll use to support the plan, the people and the process.

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Article Index

Introduction
Bad Idea #1: Pick the Technology First
Bad Idea #2: Acting on a Wrong View of the Data Warehouse
Bad Idea #3: Ignore the Political Landscape
Bad Idea #4: Leave out Critical Support Functions
Bad Idea #5: Don’t Address the Question of Data Ownership
Conclusion