When I started my career in IT leadership, I couldn't imagine ever needing a terabyte of storage. I figured a terabyte would take care of my organization's storage needs until my grandchildren were working in IT. It's a good thing I never needed a terabyte of storage, because storage back then was awfully expensive.
Niel Nickolaisen
Thankfully, because our need for storage keeps rising, the cost of storage has dropped dramatically. We just can't get enough. But why is our need for storage increasing? The answer is simple: Every day we all gain access to new sources of data. We have ERP data, which is supplemented
Requires Free Membership to View
Download Enterprise CIO Decisions for free after registering.
After registering we will email you the latest issue as well as access to our archive of back issues. Get essential editorial insights that senior IT executives need to run IT operations effectively and efficiently.
Get Enterprise CIO Decisions Now!
by customer relationship management and sales force automation data. Add to that list
our e-commerce data and data acquired from outside organizations and from public and private social
networks, and you realize: We are swimming, perhaps drowning, in data.
So, what is the best way for me to manage and use this data? I can pretty much guarantee that not all of it is usable or relevant. But how do I know which data to use? Or how do I get to it? Or how do I verify and validate it? Or how do I make it usable? Or how do I put it into the hands of the people who need it?
These questions beg for what I call an information architecture. Just as we have application architectures and network architectures, an information architecture is essential to managing data effectively. And, just as with application and network architectures, we need to plan for defining an information architecture thoughtfully. To ensure that my information architecture serves me well, I use the following approaches.
The purpose of information is to improve decision making
If it's available, I want to trademark this motto: Better decision making is the ultimate competitive advantage. If we can make better decisions over time about markets, products, operations and technology, we eventually will win in the marketplace. The reason to gather, analyze and use data is so we can make better decisions. Now, not all of the data that surrounds us will help us with that.
So, we need an effective way to filter the available data down to that data that helps us make better decisions. My filtering mechanism begins with me asking my organization two questions: What decisions would you like to make? What information would you need to make those decisions?
With the answers to these questions, I can look for the data that I can turn into the information that will enable better decision making. If the data won't lead to information that leads to better decisions, don't invest in gathering, analyzing and verifying it.
Think 'future perfect'
A way to make sure that an information architecture is flexible and survives through technology changes is to imagine that in the future, technology and the access to information will be perfect. For example, some years ago I helped a specialty retailer develop an information architecture. One of the "future perfect" scenarios we imagined was that we would be able to know the location of our customers.
Anticipating this scenario, one of the decisions we wanted to make was that we would offer loyalty-program customers customized specials as they passed near our stores. At the time, we had to back off from our future perfect and settle for asking our loyalty-program customers to check in at a register to get their special offer. Now that many people carry around smartphones that include geographic information, this retailer can implement its future-perfect decisions without redesigning its information architecture.
Treat Information as a product, and manage its lifecycle
The best advice I ever received from a peer CIO was that I should think like a product manager. Good product managers stay in touch with the market, understand market needs, develop products that meet those needs, launch the products, then manage those products' lifecycles. There are some natural phases in the life of a product, including launch, growth, maturity and retirement.
More about master data management
Pros and cons of using enterprise master data management with BI
As you define your information architecture, think like an information product manager. What are the decisions our customers would like to make? What is the best way to provide information to our customers? How should we launch our information products? And most importantly, how do we manage the lifecycle of our information products? Effective product management helps us answer these questions and keep our information architecture clean, valid and relevant.
If I am correct, and better decision making is indeed the ultimate competitive advantage, we must manage data effectively. Keeping decision making in mind, thinking about the future perfect and acting like an information product-manager have proved essential in my data management success.
Niel Nickolaisen is CIO at Western Governors University in Salt Lake City. He is a frequent speaker, presenter and writer on IT's dual role enabling strategy and delivering operational excellence. Write to him at nnick@wgu.edu.
This was first published in October 2010
Join the conversationComment
Share
Comments
Results
Contribute to the conversation