Random Curry

A real live press release!

The Data Governance eBook

A new posting by your humble narrator on the Baseline Consulting blog…

The “Temporary” Building

Ever grateful for the opportunity provided by my company to write, I give you the latest installment…

Process is Half the Story

I completed a podcast last week for SearchTechTarget.com regarding Dashboard design for business intelligence. Check it out…

Dashboard editors streamline ‘busy’ dashboards and spur user adoption

By the way – it only sounds like I’m on medication…;-)

My first post for my new employer, Baseline Consulting…

I’ve Never Metadata I Didn’t Like

(I’m not responsible for the title, so if you don’t like it, I’ll just pass that message along…)

I will be blogging occasionally for Baseline regarding MDM, governance, and assorted other BI topics. I’ll be continuing to blog about anything I damn well please here…

In Part 1 of this paper, we’ll take a look at the issue of Risk Management in the Information Technology field…

The Case for the “IT Actuary”

The success rate of business intelligence system implementation has been poor over the last twenty years. Millions of dollars are spent routinely on projects that ultimately fail to fulfill user expectations. Business users develop their own systems to operate their business analysis processes because the Information Technology group is slow to deploy solutions or the tools provided are not sufficient for managing business operations.

The common thread running through these and other major IT management issues is the inability of the staff to properly identify and quantify risk to the enterprise. This deficiency is generally due to the lack of a risk management skill set within the IT management hierarchy.  This article will use the example of shadow decision support systems to describe how risk management personnel – specifically, the concept of an actuary – can assist IT management in quantifying the risk inherent in major IT decisions and help senior business management enact and enforce more efficient management policies regarding major IT initiatives. This article will also discuss requirements for setting up such a practice, and the hurdles standing in the way of successful implementation.

The Issue

The proliferation of “shadow systems” and the IT response for management of these systems is addressed in the March 2008 Best Practices Report published by The Data Warehousing Institute (TDWI) entitled “Strategies for Managing Spreadmarts.”  This report is the latest in a series of articles describing the characteristics of non-IT business support systems and the issues they cause, published by TDWI and others. Shadow systems cause the production of inconsistent reports from different organizations within the enterprise, compromise data quality, and consume valuable personnel resources that could be used in other activities.

All of these articles and reports do a good job of describing the issues and risks of unmanaged data stores to the enterprise, but they do so in a general manner that is ultimately not useful or persuasive to the senior management personnel who are ultimately responsible for implementing controls over these shadow systems. The irony of the situation is that one of the main functions of a data warehousing organization is to provide accurate, functional measurements of business activities, but the data warehousing group often falls short of providing detailed supporting information for their claims of risk to the enterprise in many areas, including the proliferation of shadow data systems.

The lack of detailed risk analysis from IT groups is not a reflection of a disregard for the seriousness of the issues involved – the risks are well known from an anecdotal sense, but the skill set for quantifying the risks is not present in most IT departments.  Fortunately, a discipline exists for quantifying and detailing risk in business operations, but it is not generally applied to the field of information technology.

Next Time

Next time, we’ll look at the definition of “actuary,” and discuss some of the issues we come across that can be solved by actuarial concepts.

I read this article with great interest this morning:

Spreadmarts and the Ideology of BI

I appreciate perspectives that change my way of thinking, and this article does that in spades. Business Intelligence truly can be viewed as an ideology, and a fairly rigid one at that. Practitioners such as myself can be caught up in the mantra of “centralized storage for maximum efficiency” and craft all of our solutions in those terms.

I think that Western people in general tend to look at things in binary terms – good/evil, win/loss, etc. – and I think that this article does that as well. I don’t agree that centralized BI is bad, but I do agree that it must be more flexible in responding to business needs and behaviors. I submit that the most effective way of dealing with these issues is to talk in terms of risk generated for the organization. Deviation from the “standard” BI architecture makes risks larger, and that additional risk should be quantified and communicated to the business so that they can make intelligent decisions on the level of risk they are willing to carry. This way, the business users will know how items such as spreadmarts add to their risk profiles and decide on the appropriate course of action with full information.

I have more to say on the risk topic…

The end of “spreadmarts” as we know them…not a moment too soon…

How Semantics Can Revolutionize Spreadsheets

Why Business Should Be Mad as Hell at IT

Instead of answering in comments, I’ll answer here, Mark…

I agree with all of your analysis on the sorry state of business intelligence deployments. However, I think there is a fundamental flaw in your presentation: Business has treated BI like it has treated all other systems implementations: business defines what they want, throws it “over the wall” to IT, and n months later they get a system. BI systems are fundamentally different animals – they require an iterative partnership between IT and business to be successful, since the detailed requirements are generally not known in advance. Savvy BI practitioners know this, and advise business users of this difference.

If businesses are mad at IT because BI systems are not effectively delivered, they have that right – but they should be mad at themselves.