Data Governance in a Recession

What effect will a recession have on your data governance projects? Some have predicted that the nation will fall into a recession in 2008, although others disagree. In other words, it depends on whom you believe as to our economic fate in 2008. Still, with even the hint that a recession is pending, companies often move to cut costs. These cuts tend to affect major IT initiatives like data governance.

For those of us in the IT and enterprise software business, CFO-thinking runs counter to logic. During revenue-generating high times, IT tends to spend money to deliver automation that either cuts costs and/or improves productivity. So, the money spent delivers something back. However, during tougher economic times, or even when those times are presumed to be around the corner, cost cutting will be on the forefront, preventing us from fixing the inefficiencies. When revenues are good, efficiencies can be made better through IT. When revenues are bad, efficiencies are thrown out the window.

Talk of a recession may slide your plans for big projects like master data management and data governance onto the back burner. Instead, you may be asked to be more tactical – solving problems at a project level rather than an enterprise level. Instead of setting strategy, you may be asked to migrate a database, cleanse a list for a customer mailing, etc. without devoting resources to establishing a clear corporate strategy.

The good news is that times will get better. If and when there is a recession, we most certainly DON’T want to have to rewire and re-do our efforts later on. If you are asked to become more tactical, there are some things to keep in mind that’ll save you strategic frustration:

• Convince management that data governance will save money, despite the resources needed up-front. Any vendor worth their salt has case studies showing the return on investment and can help you make the case if you bring them into the process early.
• If you have to stay tactical, make sure the tools and tactics you choose on the project-based initiatives have a life in the strategic initiative. In other words, don’t cut costs on technology that won’t scale. Don’t choose tools that have limitations like lack of global support, poor connectivity, or limited performance if you’ll need those things later. Choosing these tools may hurt you when you want to go enterprise-wide; they’ll get into your plumbing and will be hard to replace. They’ll also get into the minds of your people, potentially requiring training and retraining. Even in tough economic times, you’re setting the standard when you select tools. Don’t let it come back to haunt you when times are good.
• Make sure you understand all the pieces you need to buy early in the process. Many enterprise vendors require a LOT of different packages to do real-time data quality, for example. Hidden costs can be particularly problematic.
• Make sure you understand all of the work involved, both in your project and in an enterprise implementation. There are big differences in the effort needed to get things done. Take the services effort into account during scoping.
• If cutbacks are severe but the need is still great, consider software leasing and SaaS (Software as a Service) to minimize costs. Many vendors offer their enterprise software as a service offering. If times are tough, work with the vendor on alternative ways to purchase.

On another note, I want to thank Beth from the ‘Confessions of a Database Geek’ blog for the mention of my blog this week. If you’re a blogger, you know that every mention by other bloggers gives you street cred, and I am most appreciative of that. It's great to be mentioned by one of the best. Thanks Beth!

Approaching IT Projects with Data Quality in Mind

I co-authored a white paper at the end of 2006 with a simple goal: to talk directly to project managers about the process they go through when putting together a data intensive project. By “data intensive” project, I mean dealing with mergers and acquisitions data, CRM, ERP consolidation, Master Data Management, and any project where you have to move big data.

Project teams can be so focused on application features and functions that they sometimes miss the most important part. In the case of a merger, project teams must often deal with unknown data coming in from the merger that may require profiling at part of their project plan. In the case of a CRM system, companies are trying to consolidate whatever ad hoc system is in place and data from people who may care very little about data quality. In the case of master data management and data governance, the thought of sharing data across the enterprise brings to mind a need for a corporate standard for data. Data intensive projects may have different specific needs, but just remembering that you need to consider data in your project will get you far.

To achieve real success, companies need to plan a way to manage data as part of the project steps. If you don’t think about the data as part of the project preparation, blueprinting, implementation, rollout preparation, go live and maintenance, your project is vulnerable to failure. Most commonly, delay and failure is due to late-project realization that the data has problems. Knowing the data challenges you face early in the process is the key to success.

This white paper discusses the importance and ways to best involve business users in the project to ensure their needs are met. It covers ways to stay in scope on the project while considering the big picture and the going concern of data quality within your organization. Finally, it covers how to incorporate technology throughout a project to expedite data quality initiatives. The white paper is still available today for download. Click here and see "Data Quality Essentials: For Any Data-Intensive Project"

Answer to above: All of them

Taking Data Governance from Theory to Practical Application

There is a lot of theoretical hype about data governance in the data management world, some valuable, and some not so valuable.

I personally have a hard time with any articles that try to cut data governance down to the “five most important things”. To me, it’s akin to saying, here are the five most important things you need to remember when trying to disassemble and reassemble a Boeing 757. You just can’t distill it that far and expect anything useful. Usually, this is the type of white paper produced by a marketing department run amok and useful only as a preface in the book of data governance.

Instead of trying to distill it, we need to become students of data governance and then take that knowledge and shape it for our company. It’s safe to say that the list of five, ten, or twenty five most important things to watch will be different across industry, across the company, across the globe, and across time. That’s why I have plenty to write about in this blog, and plenty to talk about on my webinars.

However, I wanted to share with you another chapter in the book of data governance that speaks to practical application. My colleague Len Dubois had a chance to interview Nigel Turner and Dave Evans from BT Design. I’ve mentioned Nigel and Dave before on my blog. They have a phenomenal story of starting up small and building increasing ROI over time. They’ve calculated huge gains in efficiency, to the tune of $1 Billion. I also credit them for the very clever Do Nothing Option.

If you’d like to hear this three-part podcast series, as told by these pioneers of data governance from Wales, please follow the link. The podcast covers the information quality challenges tackled, software selection, and lessons learned.

SAP Data Management Success Stories

I’m preparing for a web seminar on SAP data management success, and I’m really starting to look forward to it.

Moen and Oki Data will be sharing their data quality success stories with our audience. These are two very successful implementations of the Trillium Software System in the SAP environment.

My Trillium Software colleague, Laurie and I will take up only about ten minutes to first frame up and then wrap up the presentation. But the bulk of the presentation is about Moen and Oki Data and the success they’ve been able to achieve in a) quickly starting a data management program in SAP R/3, SAP ERP and SAP CRM; and b) taking the process and technology from one project to another.

If you want to join us, please click here. The webinar is on February 27th at 2 PM Eastern.

Data Governance – Does it take a platform?

I was reading through a major enterprise software vendor’s white paper and their recommendations on how to launch a data governance program. (I’m not going to provide a link - it wasn’t worth it.) Of course, much of the messaging was around buying software and the “platform” you need to do data governance… their platform.

Yet, I’m not sure it’s the wisest choice to start by buying a data governance platform. If your solution to data governance is to buy software, then you’re not really doing data governance. So much of data governance is about things like getting executives to recognize data as an asset, setting up processes, planning teams and resources, the politics of data ownership, understanding the goals of the organization and making decisions about data to support them, and so on.

Now I know it’s blasphemy for a guy who works for an enterprise software company to talk like that. In the past, I probably have been guilty of pushing the platform over process improvements. But, it’s a new day. I see real successes starting to emerge from companies who begin by taking a look at the strategy and process of data governance in the context of their business plan. Companies are beginning to soul-search a bit, before buying a platform, to know how ready they are for data governance and plan their maturation process.

Why not bring in some expertise on data governance first? Bring in the right mix of technology and business experience to build a plan, build a process and work through the politics of data governance first. There are some pretty good systems integrators out there who can help. We have partnerships with Accenture and Deloitte, for example, and they have helped set strategy on many projects.

Trillium Software also has a growing business around the business strategy of data governance. These programs are run by an arm of our professional services team called strategic services, and they too are really starting to show promise, as they work hand-in-hand with our customers to set up the processes and strategy of data governance, opening up communications between IT and management on data governance. These include the following programs:

• Data Quality Workshop - a knowledge sharing exercise that incorporates interactive group dynamics, analytics, and presentations to learn about the customer’s business, understand and share key aspects of a total data quality solution, and determine how to best solve business problems through a comprehensive data quality program. We’ll come in for a couple of days and help you through some of the data governance strategy.

• Strategic Planning Services - a service offering that helps you to build a future vision for data quality that optimizes processes and improves data quality enterprise-wide. This service focuses on future data quality strategies such as dealing with complex enterprise data quality deployments, expansion of data quality initiatives and the effects of mergers and acquisitions on the business.

• Data Governance Planning – This service helps organizations with developing, refining, and supporting their data governance strategies and programs. It recognizes that data quality by itself does not define data governance. Rather, it also includes a focus on business processes and people to achieve success.

If this is something that your company needs, send me an e-mail and I’ll set it up for you, or find out more here. These workshops are particularly helpful if you have some key stakeholders dragging their feet on data governance. They can help you all get on the same page.

Does it take a platform to do data governance? Maybe, but data governance is a far-off dream for many companies. In this case, it takes a lot more than technology to fulfill a dream.

Mainframe Computing and Information Quality

Looking for new ways to use the power of your mainframe? My friend Wally called me the other day and was talking about moving applications off the mainframe to the Unix platform and cleansing data during the migration. “Sure, we can help you with that.” I said. But he was surprised to hear that there is a version of the Trillium Software System that is optimized for the Mainframe (z/OS server). We’ve continually updated our mainframe data quality solution and we have no plans to stop.

Mainframe computers still play a central role in the daily operations of many large companies. Mainframes are designed to allow many simultaneous users and applications access to the same data without interfering with one other. Security, scalability, and reliability are key factors to the mainframe’s power in mission-critical applications. These applications typically include customer order processing, financial transactions, production and inventory control, payroll, and others.

While others have abandoned the mainframe platform, the Trillium Software System supports the z/OS (formerly known as OS/390) environment. Batch data standardization executes on either a 64-bit or 31-bit system. It also supports CICS, the transactional-based processing system designed for real time processing. z/OS and CICS easily support thousands of transactions per second, making it a very powerful data quality platform. The Trillium Software System can power your mainframe with an outstanding data quality engine, no matter if your data is stored in DB2, text files, COBOL copybooks, or XML.

The Trillium Software System will standardize, cleanse and match data using our proprietary rules engine. You can remove duplicates, ensure that your name and address data will mail properly, CASS certify data and more. It’s a great way to get your data ready for SOA on the mainframe, too.

My hats off to Clara C. on our development team, who heads up the project for maintaining the mainframe version of the Trillium Software System. She’s well-known at Trillium Software for her mainframe acumen and for hosting the annual pot-luck lunch around the holidays. (She makes an excellent mini hot dog in Jack Daniels sauce.)

I’m not sure whether Wally will stick with his mainframe or migrate the whole thing to UNIX servers, but he was happy to know he has an option. With an open data quality platform, like the Trillium Software System, it’s not a huge job to move the whole process from the mainframe to UNIX by leveraging the business rules developed on one platform and copying them to the other.

Oracle Data Integration Suite - Trillium Software Inside

Finally! Finally, I can talk about the exciting news regarding Trillium Software’s partnership with Oracle. It’s a perfect decision for Oracle to begin working with Trillium in the data integration market, combining Sunopsis technology with Trillium Software technology to address some of the competitive challenges of IBM and the Webshere platform.

Trillium Software has long been a supporter of the Oracle platform, first offering batch technology for cleansing Oracle databases. A few years ago, we began offering direct support for Oracle’s older data integrator, OWB. Now, this integration with ODI is going to serve Oracle customers with excellent data quality within a superb data integration platform.

Trillium Software prides itself in it’s our connectivity into major enterprise applications. Here are a few of the most popular ones:

• SAP - SAP R/3, SAP CRM, SAP ERP and SAP NetWeaver MDM.
• Oracle - OWB, ODI, Siebel eBusiness, Siebel UCM, Oracle CDH, and Oracle eBusiness Suite.
• Ab Initio
• Siperian

In addition, we still have quite a few customers on the Informatica platform, and we continue to support those customers, despite the fact that Informatica has had a competitive data quality solution since its acquisition of Similarity Systems. We even maintain our integration with IBM Websphere, despite IBM’s acquisition of Ascential, who had acquired data quality vendor Vality. Still, we have a significant number of users who are using Datastage with Trillium Software and don’t want to switch.

Why support all these integration points when other vendors don’t? It’s where the reality of the marketplace meets product development. Let’s face it, large companies most often don’t run a single application platform across their entire enterprise. Most have a mixture of IBM, Oracle, Siebel, and many other enterprise vendors. Sometimes, this makes perfect sense for the organization. The heterogeneous enterprise often occurs when the application vendors can’t meet all the needs of the organization. So, for example, SAP ERP may meets the need of manufacturing, but Siebel better meets the requirements of sales and marketing.

On the other hand, it makes sense to standardize the data platform of your company. If you can plug the same rules engine into any of these platforms, data quality is more easily a simple component of corporate governance. Now you don’t have to hire staff to operate and maintain multiple data quality tools. Now, you won’t have to try to tune one data quality tool to make it behave like another. It is much easier to achieve a company-wide gold customer master record with a single information quality platform like Trillium Software.