Informatica Perspectives

Over the past few weeks we’ve been talking to Informatica customers about cloud integration at the Informatica 9 World Tour events. In most of the cities, we’re hosting a Cloud Breakfast to dive in to what Gartner has listed as one of the top 10 strategic technologies for 2010. Not surprisingly, interest has been widespread. Attendees include people in IT and line of business (LOB) roles; people with PowerCenter skills and long-time Informatica Cloud customers; CRM administrators and IT architects; sales and marketing operations; ISVs and quite a few consultants.

One thing that they all have in common is that they’re thinking about the opportunities and challenges that the shift to cloud computing represents. As one attendee put it, “we can either get on the train or get run over by it!”

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The cover story on the March 8th issue of Computerworld is “Swinging Toward Centralization”. It talks about the pendulum moving toward IT consolidation as organizations strive to save money and improve controls. This article is not alone. A growing number of analysts are talking about consolidation, Lean IT practices, and taking “a production line approach to integration”.  When you combine all this rhetoric with the industry fundamentals, the stage is set for 2010 to The Year of the ICC. [Read more]

While the market is showing signs of recovery from the "Great Recession" most state budgets have been feeling the squeeze from the lag in recovery. In a recent article titled The Sorry State of Finances, Liam Denning explained that, "55% of state revenue, before federal transfers, comes from personal and corporate income tax." Denning also stated that, "the first three quarters of 2009 were the worst for state tax since at least 1963."

There is an apparent lag between recovery in the private sector and a state receiving tax revenue. So what can states do about this problem while they suffer in the red? Mr. Denning said, "Since states can't run general funding deficits, closing gaps mean raising taxes, cutting services and resorting to one-time measures." Mr. Denning's list of solutions is certainly accurate, but does it include all options that states have? What about employing new technology to discover fraud or recover uncollected revenue? [Read more]

This is the last of the Data as an Asset series and what better way to wrap up the theme than with a view to the future. As stated by Thomas Redman, author of Data Driven, “Your company's data is a key business asset, and you need to manage it aggressively and professionally.” The future vision then is around Agile Data-Driven Enterprises. [Read more]

Continuing with the Data as Asset series, in this posting I explore the negative side and what can happen when data becomes a liability. Physical assets such as buildings, equipment, or even money, can become a liability if not managed properly; buildings can become unsafe to work in, machinery can be dangerous to operate, and business investments can turn into money-sinks. Similarly, data and information systems can also be assets that provide economic value to the enterprise or they can be liabilities that destroy value or put the business at risk if not managed well. Here are three common scenarios. [Read more]

My last post on this theme A Market-based Approach To Valuing Data, introduced the idea of establishing an internal data economy as a way to value and manage data assets. Here now is a specific scenario for how this could work. I apologize in advance for the length of the posting, so please bear with me. The level of detail is necessary to demonstrate how an internal market can function in a practical manner. [Read more]

As per discussions in prior postings on Managing Data as Assets, yet another method for valuing assets is to use market prices (mark to market). This method works best in a market for a homogeneous product where no individual buyers or sellers can affect those prices by their own actions. Securities such as stocks and bonds fall into this category. If you own 1,000 shares of Informatica stock for example, you know exactly what they are worth at any time since there is a highly liquid market for them – it doesn’t matter what you paid to acquire the securities (except for tax purposes) and you don’t have to sell them to determine their value – you only need to look at what they are trading for at the moment. [Read more]

Continuing from my prior post Valuing Data Using Managerial Accounting Practices, you don’t actually need to put data assets on the public balance sheets to achieve the desired management focus You could use internal management accounting methods such as EVA (Economic Value Add). In EVA, operating costs that have long-run benefits (such as R&D, brand advertising, certain IT investments) are recorded as assets rather than operating expenses. EVA is generally calculated by line-of-business as EVA = NOPAT – (WACC * NOC)

• NOPAT = Net Operating Profit After Tax
• WACC = Working Average Cost of Capital
• NOC = Net Operating Capital [Read more]

Some executives have told me that 40 to 70 percent of their IT budgets are devoted to integration. These are the same ones that still tackle integration on a project-by-project basis, causing unnecessary expense, waste, risk, and delay. They struggle with integration “hairballs”: complex point-to-point information exchanges that are expensive to maintain, difficult to change, and unpredictable in operation.

The solution is two new services that Informatica announced this week; Integration Factory Implementation and Automated Deployment Framework. These services compliment the Informatica platform and are another outcome of the work that went into creating the Lean Integration book which will be available in book stores soon (visit www.integrationfactory.com if you can’t wait). [Read more]

As a follow up to my previous post Data As An Asset Part 1 – Should Data be on your Balance Sheet?, let’s get back to the balance sheet question and ask it differently – how COULD an organization go about formally valuing their information assets?

There is a relatively straight-forward way to establish the initial value of data assets by simply adding up the costs associated with creating the data. In other words, we could quite easily figure out what it costs to initially create the data – the acquisition cost. Once we have the initial value established, we could use standard depreciation models such as straight-line or accelerated depreciation to account for the deterioration in the value over time. [Read more]