Data Doghouse - performance management, business intelligence, and data warehousing

Data is the Problem, not Excel

It’s funny that Forrester’s Boris Evelson recently received a slew of comments from data warehousing and business intelligence pros wondering why they hadn’t included an evaluation of Excel as a business intelligence tool. Boris goes on to explain why Excel doesn’t work as a standalone BI tool.

Here’s my take on the subject:

Like it or not, the most widely used BI tool today is the spreadsheet. If you are a BI or data warehousing manager, you need harbor no illusions that you are gathering and manually entering data into spreadsheet. Furthermore, you need to work with the logic captured in Excel spreadsheets and enable this logic to be used for analysis and decision support.

What’s the problem? Simple. The proliferation of custom-built reports with unstructured data pulled from who-knows-where using self-serving metrics brings into question the value of the information available.

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Upgrading your data integration efforts to enable Business Intelligence (BI) 2.0

People have been using the term “business intelligence 2.0” for a few years, but it’s described in different ways. In Business Intelligence 2.0: Simpler, More Accessible, Inevitable Neil Raden says:

"…the current era of BI is coming to an end and will be succeeded by a BI 2.0 era that promises simplicity, universal access, real-time insight, collaboration, operational intelligence, connected services and a level of information abstraction that supports far greater agility and speed of analysis. The motivation for this "version upgrade" for BI is the need to move analytical intelligence into operations and to shrink the gap between analysis and action."

Charles Nichols writes, in BI 2.0: The Next Generation that:

"BI 2.0 is a term that encapsulates several important new concepts about the way that we use and exploit information in businesses, organizations and government. The term is also intrinsically linked with real-time and event-driven BI but is really about the application of these technologies to business processes."

BI 2.0 is not really about a new generation of BI tools to perform analytics but getting more comprehensive, consistent, correct and CURRENT data.

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Master Data Management: Engineering or Product Design Firms

Maintaining product lists is often cited as a great example of Master Data Management (MDM). Many companies that manufacture or sell products need to get a consistent list of products for a variety of business reasons. The business value includes tracking what you sell to customers and also how you manage your supply chain. Product firms create products organically (internally) and through acquisitions. In both cases, each product line has, at least for part of its life, been operated as a separate business. At some point in the product life and sales cycle, business conditions dictate a transition into the company's product portfolio. Although managing product lists is not always a simple task, it is only the tip of the iceberg for companies that design or engineer products. These companies have a need for a more complete PIM (Product Information Management) solution that extends far beyond simple product lists.

If you design or engineer products, then you need to track product designs and configurations that evolve and change over time. This applies to many manufacturing industries from high tech, consumer products, defense, and automobile to even farm machinery. These designs and configurations are likely scattered across many databases and often unstructured data sources. This data is not stored in your classic data warehouse (DW) or integrated through your run-in-of-the-mill ETL tool. You need to think outside your typical DW effort and determine how to get that data integrated into your PIM solution.

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HealthCare Improvements Through Master Data Management

Healthcare is one of the last industries where you hear the term MDM (Master Data Management) mentioned. Most IT industry analysts, software firms and consulting organizations are geared towards your typical company that sells products to people or businesses. MDM examples are always getting a master list of products or cleansing your way to a consistent list of customers, which is not exactly the mindset of healthcare organizations. But lack of MDM is precisely what is adding untold costs on healthcare organizations (and ultimately on all of us) and inhibiting these organizations from improving the quality of health care services at an affordable cost.

Let's divide the healthcare industry (simplistically) into insurers and providers (we will position pharmaceuticals, biotechs and medical device companies as life sciences). Many of the large insurers have invested in data warehousing and data integration, but smaller insurers, i.e. regionally based HMOs (healthcare maintenance organizations) and healthcare providers, such as hospitals and physician groups, have fledgling efforts or have been bogged down in many of the issues below.

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Business Intelligence Strategies in a Down Economy

There is a lot of worry on Wall Street and Main Street these days. Are we in a mild or severe recession? Is it the next Great Depression? How long will it last? No one knows the answers to these lofty questions, but Forrester Research has been busy recalibrating on the impact the economy is having on IT spending.

First, the good news, IT spending was better in the first half of this year than expected. The bad news, IT spending is being hit adversely now and probably into 2009. According to Forrester Research:

“The economy's affect on IT spending is evident in some specific data points contained in the report: Forty-three percent of firms have already cut their overall IT budgets in 2008 in reaction to the slow down in the global economy, while 24 percent of firms have put discretionary spending on hold. Twenty-eight percent of respondents said the economy has had no impact on their IT budgets.”

“Forrester: Impact Of Economic Downturn On Tech Spending Varies By Region And Sector”, Forrester Research, September 9, 2008

Even under the best circumstances it’s important to maximize the value from your BI/DW projects.  But with these conditions it becomes even more of an imperative.

No one can afford to be sloppy or wasteful in their business intelligence and data integration strategies. Cost cutting and getting by with what you have is the norm.

But mistakes are expensive. Businesses, now more than ever, need to understand who their current and potential customers are as well as how much revenue and profit each product or service line generates. This demands current, consistent, clean and comprehensive data.

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“IT’s Wonderful Life” – Yes, IT is

Tom Davenport has a great post “IT’s Wonderful Life”  in his interesting “The Next Big Thing” blog. With the backdrop of the holiday season and the sentimental movie “It’s a Wonderful Life” with Jimmy Stewart, he muses in his post about the positive things IT has contributed to companies. He cites Wal-Mart (WMT), various airlines and the banking industry as all having benefited from IT’s efforts.

I’d like to take his praise a step further by observing that all his examples are great references for the business benefit of enterprise data warehousing and enterprise data management.

All of these companies have positioned data as an enterprise asset that, when integrated and transformed, enables them to manage far better than if they were simply operating by “gut feel.”

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Your 2008 Data Integration Plans, Part 5:Adding Real-Time Business Intelligence to your Information Portfolio

There are two things I hate in discussions about real-time business intelligence. 

First, pundits cite great examples of the business need for real-time BI, but then go overboard by assuming that every report and analysis needs to be done using real-time data.

The reality is most analysis is done looking at specific timeframes (daily, weekly or monthly), trending (YTD) or period over period analysis. Up-to-the minute data would be discarded or create “noise” in analysis. The cost both to load and then to filter out the irrelevant real-time data for analysis is much greater than most enterprises are willing or able to spend. And it just makes things too complex.

The second area that riles me is that people, even high powered architects who should know better, oversimplify real-time BI. As I mentioned when I discussed SOA, too often real-time BI is seen as solely accessing data rather than involving more complex data integration. Other than accessing very limited data such as data related to an individual customer, much reporting and analysis involves gathering and transforming data from many locations. This requires data integration rather than just data access.

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It’s the data (integration) that enables BI

Ben Worthen in his Wall Street Journal “Business Technology” blog “The Death of Gut Instinct” discusses how:

“For the third year in a row, CIOs (surveyed by Gartner) said that ‘business intelligence software,’ which organizes and analyzes the data companies collect, was their top tech priority.”

Ben further comments:

“…information-technology departments have used those (previous BI) projects – which usually involved building a giant data repository and installing software that can look for trends in that data – as stepping stones to greater glory.”

I am very excited by the continuing growth of business intelligence and performance management efforts across enterprises of all sizes and all industries. There is real business value to these projects. Business people realize it, not just IT folks.

There is something, however, that concerns me because it is either being left unsaid or, worse, being taken for granted. Business people, and in many cases industry analysts and pundits, associate an IT project with the customer facing software. An IT project is then considered a Business Objects, Cognos or Hyperion project rather than, say, a financial data warehouse project.

>>> Read the rest of "It’s the data (integration) that enables BI" on the Informatica Enterprise Data Management blog.

The Disconnect with Data Integration and SOA

Many companies are building Service Oriented Architecture (SOA) initiatives apart from data integration projects. Since information is one of the key ingredients to creating business value from SOA initiatives, how could this disconnect be occuring?

A few characteristics of IT projects are causing this application stovepipe to happen.

First, IT has, for decades, continually developed applications or implemented infrastructure on a project-by-project basis. Rather than viewing their enterprise holistically, companies continually look at their projects with a narrow focus. Although this limits scope and maybe improves a project’s chance to be completed, it is shortsighted since too much overlapping or conflicting work occurs.

Second, IT has a tendency to segment its work by the technology that is used rather than what processes are being built.  IT assumes that since SOA is “new,” it must be different than all the “mature” data integration software technologies such as ETL, EAI and EII.

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MDM is not a product

Rob Karel, Forrester Research, Inc. (FORR), wrote an interesting year-end review of his 2007 Master Data Management (MDM) forecasts in the Forrester Information Management blog on December 26th.  Rob hits on a few themes that I am constantly discussing with clients and colleagues:

“While all of the product development, marketing, and M&A activity coming from the MDM vendors is interesting and entertaining, the most valuable and insightful information about the evolution of the MDM market comes from the Forrester customers I speak to every day. Unlike my coverage of more mature data integration technologies like ETL where vendor selection is the most common question asked, I rarely field questions about MDM vendor selection. Regarding MDM, these customers are more concerned about data governance, organizational readiness, architectural strategy, business case development, prioritization, and the biggie — do we really need to worry about MDM? If so, why?

What does it all mean? I'm happy to report that it means you are asking the right questions at the right time. …be sure your organization is prepared to deal with the cross-functional and technical complexities of adopting a master data management strategy….”

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