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William McKnight

Hello and welcome to my blog!

I will periodically be sharing my thoughts and observations on information management here in the blog. I am passionate about the effective creation, management and distribution of information for the benefit of company goals, and I'm thrilled to be a part of my clients' growth plans and connect what the industry provides to those goals. I have played many roles, but the perspective I come from is benefit to the end client. I hope the entries can be of some modest benefit to that goal. Please share your thoughts and input to the topics.

About the author >

William is the president of McKnight Consulting Group, a firm focused on delivering business value and solving business challenges utilizing proven, streamlined approaches in data warehousing, master data management and business intelligence, all with a focus on data quality and scalable architectures. William functions as strategist, information architect and program manager for complex, high-volume, full life-cycle implementations worldwide. William is a Southwest Entrepreneur of the Year finalist, a frequent best-practices judge, has authored hundreds of articles and white papers, and given hundreds of international keynotes and public seminars. His team's implementations from both IT and consultant positions have won Best Practices awards. He is a former IT Vice President of a Fortune company, a former software engineer, and holds an MBA. William is author of the book 90 Days to Success in Consulting. Contact William at wmcknight@mcknightcg.com.

Editor's Note: More articles and resources are available in William's BeyeNETWORK Expert Channel. Be sure to visit today!

Recently in Return on Investment Category

I made it to the Oracle Collaborate show this week in Orlando.  I presented a case study presentation on a MDM initiative.  I spent several hours in the expo hall talking with people in some interesting concepts.  A couple of themes stood out as being somewhat new to being on an expo hall floor.

1.       Lifecycle data support

There continues to be evidence that new approaches are necessary to keep data alive and do it at a lower cost than keeping "all data online everywhere".

Sure, we've got major compression and columnar orientation to compress complete rows of data everywhere it resides.  However, we usually don't usually want to carry production data loads in the development and test environments, yet we need data that approximates production data there.  One feature of IBM Infosphere Optim, among others, is the ability to get a representative sampling of production data into those environments according to the direction you set. 

Also, there were the archival features of TierData, which smartly determines which production data, even columns, you can safely archive to improve the overall performance of the application.

2.       Part Time Help

The commoditization of certain functions that were always just there in the shop and taken for granted continues.  For better or worse, services like SmartHelp from Circular Edge and DBA on Demand from SmartDog give their clients flexible work arrangements for a variety of technical enterprise functions. 


Posted April 16, 2011 2:35 PM
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The article, Gartner: Business intelligence ROI, value a matter of mind over money, begins with "Determining the return on investment (ROI) and value of a business intelligence (BI) software investment is often an exasperating task, but not an impossible one, according to one Gartner analyst."

I completely agree, but I also feel it's a matter of maturity, and mature BI environments can get there. I also believe it's a best practice to measure and that it has a high correlation to overall "success", whether success is defined by the numbers or otherwise.

Following are some focuses, in order from healthiest to unhealthiest, that business intelligence programs fall into. As we progress through the focuses, you will notice the focus gets further and further away from the user.

Business Focus #1: Return on Investment
ROI is the holy grail of focus for business intelligence. Those teams that focus on achieving it have learned what business intelligence is all about. Studies have shown that driving toward ROI highly correlates to self-reported program success scores. The focus on ROI just seems to encourage the development team to work backwards to doing the right things day in and day out for the ultimate arbiter of success - the bottom line. Ultimately, to claim this focus, a team must have a great handle on the succeeding focuses well.

Business Focus #2: Data Usage
Those programs that don't measure ROI or are too removed from business processes that drive ROI but still want a business-focused BI program focus on the usage of the data. The objective here is increasing numbers and complexity of usage. With this focus, user statistics such as logins and query bands are tracked; however, little is understood about what the users ultimately do with the results.

Business Focus #3: Data Gathering and Availability

Under this focus, the business intelligence team becomes an internal data brokerage, serving up data for the organization's consumption. Users are not tracked because success is measured in the availability of the data.

In these environments so removed from usage, it is often a struggle for the users to leverage the data. It is not unusual to find a host of downstream processes (i.e., Excel, Access) operating to "fix," "clean" and make this data usable. Users may have grass roots efforts underway to utilize each other's "code."

These environments often come about when there is high complexity in the data extraction and movement layer of the architecture. While it's an accomplishment to deliver the data in these environments, the team should not neglect the need to deliver business intelligence, which requires the accoutrements related to usage to be in place -- such as governance, stewardship and a public relations program.

User satisfaction with such programs begins to fade once they are left to deal with the limitations of delivered raw data.

Technical Focus #1: Key (Technical) Performance Indicators
This is the technical counterpart to a business focus on data usage, but it is not as effective overall. There can be an especially large number of KPIs for the business intelligence program in the area of ETL. These are analogous to the metrics you might place in the operational meta data -- up time, cycle end times, successful loads, clean data levels, etc. While important, they do not comprise the end game.

Technical Focus #2: Adherence to a Guru Approach
One of the ultimate disservices business intelligence teams can do is to spend their budget primarily making sure the architecture adheres to a book standard - as opposed to what works for the users.

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Technorati tags: data warehouse, business-intelligence, information management


Posted April 7, 2008 1:15 PM
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Below are some learnings and tips on BI/DW ROI from Neil Freake, Senior Manager of BI/DW at Scotiabank, a client who I had the privliege of presenting with yesterday at the Shared Insights show. The presentation was titled "Providing ROI with Business Intelligence." This was an additional slide so it's here, as promised, for the attendees... and all of you.

- Financial Models need to factor in attrition rates
- Calculating “lift” is often not a viable argument (wholly dependent on assumptions)
- Benefit is based on Profit NOT Revenue (ergo…understand margin calculations)
- Financial Models must be more accountable when defining costs (i.e., SOX)
- First Run Cost Estimates are always off +/- 25%
- Payback Calculation – two camps
- Cost Camp: begin to calculate as soon as you incur costs through cumulative life of benefits
- Benefit Camp: Calculate payback after project has been implemented (Not recommended or realistic)
- Soft Dollar benefits are easier to argue / more difficult to prove
- Hard Dollar benefits are rare, more difficult to argue and almost impossible to prove.
- Most organizations use a 10% interest rate when calculating NPV
- How well you define your assumptions will dictate how well your model stands up to financial scrutiny
- Every financial model has weaknesses (highly subjective)
- Would have to be in a lab to prove benefits
- Double dipping benefits – most common error in business cases (who has the right to claim a benefit?)
- ROI is purely an internal (and sometimes external) marketing tool
- The higher the dollar amount the more scrutiny your project will face


Posted August 17, 2006 12:35 PM
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