Rush To Records Management Certification

  By Brian W. Hill

As we get closer to ARMA International's Annual Conference & Expo in Orlando, Florida, later this week, it’s likely that we’ll hear a lot about US Department of Defense (DoD) records management certifications. Some enterprises treat DoD 5015.2-STD V3 certification as a “check box” item for RFPs, but for others, such as US federal government agencies, these certifications are required.

Q3 2009 survey data show that in making future records management purchasing decisions, DoD 5015.2-STD V3 certification plays a key role. Forty-two percent of records management stakeholders rate DoD 5015.2-STD V3 (baseline) certification as "important" or "very important" in buying decisions. The comparable figures for DoD 5015.2-STD V3 (classified) and DoD 5015.2-STD V3 (Freedom of Information Act/Privacy Act) are 24% and 34%, respectively (see Figure 1). The survey data show that these certifications are more important for government (local, state, and federal) organizations, but not dramatically so. In comparison with their non-government counterparts and with some variation across the specific DoD 5015.2 certifications, 5% to 10% more government records management decision-makers rated these certifications as "important" or "very important."

 

The DoD standard specifies a large number of detailed requirements that electronic record-keeping systems must meet. In order to achieve certification, systems must successfully pass all mandatory requirements. Enterprises, along with vendors, clearly recognize the importance of these neutral, third-party assessments. For example, in July through September, Alfresco, Autonomy, CA, HP, Hyland, Iron Mountain, and Open Text all completed certification testing for DoD 5015.2 V3.

Join me today at 1:00 p.m. Eastern for a Forrester teleconference on the changing records management market. I’ll touch on records management certification and we’ll cover user expectations, market trends, and obstacles along with vendor evaluations, SaaS and hosted deployment trends, and enterprise recommendations. For further information and to sign up, click here.

The Webcast will run from 1:00 p.m. EDT to 2:00 p.m. and will include a question-and-answer session.

Service-Oriented Analytics: Tapping into the Predictive Smarts of Your Entire Organization

By James Kobielus

Advanced analytics is a key competitive weapon of companies everywhere. Visionary organizations are those that take a future-facing, analysis-driven perspective on new challenges. They do this by grounding management forecasts in solid historical information sets, leveraging and extending companies’ existing investments in data mining and predictive modeling.

To become truly future-focused, organizations must build out their predictive muscles through deepening commitment to these and other advanced analytics technologies, which also include interactive visualization, multivariate statistical analysis, text analytics, and massively parallel enterprise data warehousing. However, enterprises must be careful not to adhere to the common practice of implementing advanced analytics tools in tactical, application-specific silos. One of the downsides of this traditional practice is that diverse predictive modeling teams can find it difficult to share their deep domain expertise, best statistical approaches, and most powerful data exploration and visualization features.

How can companies realize the transformative potential of predictive analytics for business success? For starters, you must get rid of siloes that fragment your data mining initiatives into separate camps. You must also build a bridge between your data mining operations and the teams that manage your text analytics, business intelligence, complex event processing, and business process management efforts. And the key approach for silo-smashing is service-oriented architecture (SOA).

At first glance, SOA may seem like a foreign topic to many analytics professionals, but it shouldn’t be. In the broadest perspective, SOA refers to best practices for encouraging greater reuse, sharing, and cross-platform interoperability among key business resources. Typically, one associates SOA with reuse of one specific type of resource: application functionality that is distributed across heterogeneous, networked platforms. Nevertheless, key SOA principles—such as standards-based service virtualization, reuse, brokering, and governance—are as applicable to predictive models as to any other resource that lives online.

Predictive models empower your product managers, marketing specialists, risk managers, process analysts, senior executives, and other personnel with access to sophisticated forecasting, time-series analysis, and scenario-testing tools. Each model is a statistical encapsulation of your business’ current view of the future in some specific application, subject, or decision-support area. Incorporating the expertise of subject-matter experts, these models allow organizations to gauge the potential impact of future projects, campaigns, and other initiatives, and also to adjust execution of these initiatives in mid-stream.

Predictive analytics need not be a purely blue-sky planning tool. This technology can sit at the core of your SOA strategy, and leading-edge enterprises are in fact doing that. Companies in such verticals as financial and telecommunications are embedding predictive logic deeply into data warehouses, business process management (BPM) platforms, complex event processing (CEP) streams, and operational applications.

What will it take for your company to fully align your advanced analytics efforts with your SOA strategy? Most important, Service-Oriented Analytics requires an executive-level commitment to becoming a predictive enterprise on all levels. From the perspective of your existing predictive modeling teams, this will require an ongoing focus on collaboration across business, function, and subject domains. You should create a culture and offer incentives that encourage modeling professionals to reuse each other’s expertise on problems that cross multiple domains.

Reuse is everything. Here are some high-level guidelines for establishing a reuse-friendly Service-Oriented Analytics practice in your company:

• Reuse modeling best practices:  Start by consulting Forrester’s report on setting up a Business Intelligence Solution Center (BISC), which we defined as “an institutional steward, protector, and forum for BI best practices.” Given that predictive analytics is a key segment of BI, you will find it necessary to incorporate this technology into your BISC’s scope.
• Reuse modelers: Cultivate a professional cadre of predictive modeling experts who are more than just wizards in advanced statistics and mathematics. Encourage subject-matter experts in all business areas to undertake predictive modeling projects and to team with modeling experts in other projects, applications, and business units. Provide incentives for modelers to regularly move between business units and subject domains, thereby spreading their expertise throughout the enterprise.
• Reuse models: You should begin to investigate predictive-model governance tools, which support version control, check-in/check-out, and other controls over models created in and imported from diverse tools. Model governance tools—from vendors such as SAS, SPSS, and KXEN--facilitate reuse, consolidation, combination, and cross-synthesis among disparate models. And you should also investigate options for embedding predictive models within BI, BPM, and other operational applications, thereby leveraging your growing analytic asset into new deployments.

As you deploy predictive models into operational applications, you should provide other applications with SOA-based access to them through Web services, Web 2.0, and other standardized interfaces. In that way, you will be creating a critical bridge to your application development teams and be creating a thoroughly Service-Oriented Analytics environment.

Your first steps down this road are clear. Forrester will be happy to assist you in developing a detailed enterprise roadmap for Service-Oriented Analytics. In so doing, you’ll be better able to tap into the future-facing analytic expertise that exists throughout your business.

Microsoft Office 2010: The Odyssey Continues

by Sheri McLeish

Sequels never can match the thrill of the original. But the good ones offer a compelling story of their own, develop familiar characters, and introduce something new and exciting. Last week Microsoft gave developers a backstage pass to preview Office 2010, due out in the first half of next year. The drama unfolds with Microsoft and Google waging a multi-front war with each other in search, browsers, productivity tools, and, soon, operating systems. Glimpses of the fourteenth iteration of Office reveal Web-based lightweight apps along with capabilities geared at improving collaboration, multimedia content development, and email management.

Can Office 2010 save the franchise? Or will a simpler, better customer experience from Google draw in a bigger audience before next summer? And what does it mean for the bit players, independents, and sleepers like the Open Office suites from IBM/Lotus, Novell, and Sun, or for Adobe, Zoho, Thinkfree, Corel … that’s a lot of competition for a sluggish software market that Forrester sees as being down by 5% or more for the year.  The glimmer of hope for software vendors will likely come from subscriptions revenue for software-as-a-service (SaaS) products in 2010, which Forrester projects to grow by 7.5%.

Microsoft wants to lead that growing SaaS market. For enterprises, what’s notable about the Office 2010 story is that Office Web apps can be on-premise or hosted. The lightweight Web browser versions of Word, PowerPoint, Excel and OneNote will be free for consumers through Windows Live. Pow! But the bigger deal for enterprises is the option to host Office Web apps on-premises as annuity customers as well as via a hosted subscription through Microsoft Online Services. This option isn’t offered by Google today and, for the moment, may be what makes Office Web apps a hit in the enterprise.

To date, Microsoft’s dominance in large businesses remains mostly intact, with 57% of firms running Office 2007 and 80% supporting some version of Office.  Combined, the alternatives make up less than 8% of the enterprise market, according to Forrester’s March 2009 North America, Europe, And Asia Pacific Desktop Innovation Online Survey. And of those Forrester surveyed, 78% said they have no plans to look for an alternative to Microsoft Office. Real barriers remain for alternatives, from concerns about content control and security, sunk license costs, and online/offline issues for Web-based tools to fear of rejection by business users. Like it, love it, or not, people have a comfortable, familiar relationship with the Office apps. And that’s a critical edge Microsoft must maintain.

Technology Populism is fueling the collaboration and mobile collaboration markets and blurring the lines between work/life boundaries.  The influence of consumer experience can be equally powerful if harnessed by Google for email and productivity. Most enterprise IT departments rely on the feedback of their business users to measure the value of their productivity tools. Forrester data also shows upgrades generally driven by business demands (34%), because current tools are no longer supported (24%), are no longer compatible (16%), or because the culture demands it (15%). By promoting free access to Web-based tools, Microsoft seeks the sway of the public. Office 2000 ends support this month; Microsoft needs to get those firms on board with 2010 somehow. What will your firm do? What are your barriers to upgrading Office or moving to an alternative? Now is a good time to clarify your firm’s strategy, because 2010 looks like it could be a blockbuster year for buyers prepared to negotiate.

BI Mashup Maturity Model? Oxymoron? Au Contraire Mon Frère!

By James Kobielus

In one of my recent tweets, I commented that Forrester has developed a maturity model for enterprise adoption of mashup-style, self-service development of business intelligence (BI) applications. Indeed, we have, and it will appear in my forthcoming Forrester report, “Mighty Mashups: Do-It-Yourself Business Intelligence for the New Economy.”

Another tweeter--an astute, but sadly, non-Forrester BI analyst--scoffed that “BI mashup maturity model” is an oxymoron. Respectfully, I must disagree. Enterprises are adopting self-service BI approaches for many reasons--principally, to cut costs in a tight economy, to unclog the development backlog, and to speed delivery of actionable, targeted intelligence to decision makers. Also, companies are providing users with BI tools to do interactive, deeply dimensional exploration of information pulled from enterprise data warehouses (EDW), marts, cubes, transactional applications, and other systems. Furthermore, organizations everywhere have adopted browser-oriented BI environments that leverage the full Web 2.0 interactivity and collaboration.

Sitting at the convergence of those trends is BI mashup, which Forrester sees as the new paradigm for truly pervasive decision-support systems. What throws off some people is the term “mashup,” which sometimes gets pigeonholed as simply referring to using, say, Google Maps to display geocoded performance metrics and sundry Internet-sourced data in a browser-based dashboard. Yes, BI mashup encompasses that approach to presenting and integrating diverse data, but its application is much broader.

Just as important, BI mashup is not bleeding-edge. Rather, BI mashup leverages the in-memory BI clients, semantic virtualization layers, data federation middleware, automated data discovery, and other next-generation BI tools and platforms.

No one vendor or user has yet put together an end-to-end BI environment that is entirely focused on mashup-style self-service development. However, Forrester sees the BI industry converging toward as mashup-oriented architecture over the coming 2-3 years. With that in mind, we sketched out a BI maturity model that encompasses the following four levels (the first 3 of which are represented in case studies in the upcoming report):

• Level 1: Lightweight presentation mashup against transactional applications: This basic maturity level is for companies that have no prior BI or EDW; have little in-house BI expertise; and are comfortable with allowing casual users to use their browsers to customize parameterized reports from data from packaged business applications.                                                                
• Level 2: Deep presentation mashup against EDW: This level is for organization that do have prior BI and centralized EDWs, but have an understaffed BI development group and/or  power users and data modelers urgently require the ability to mashup and explore historical and current data within sophisticated BI workspaces.
• Level 3: Full BI mashup in federated environment: This level is for organizations that have decentralized, dynamic data management environments, and have the expertise to design reusable, composite data services to seamlessly mashup internal and external information.
• Level 4: Full collaborative mashup with IT governance: This level is for organizations that want to encourage subject  matter experts and operational users to collaborate on analytics created through mashup, but who are also concerned that all mashups be controlled, governed, and monitored in accordance with enterprise policies and best practices.

As I said, it will take a few years before we see a substantial number of enterprise case studies that implement the pinnacle of collaborative mashup with tight governance. Nevertheless, when you follow the evolution of next-generation solution portfolios from leading BI vendors such as SAP, IBM, Microsoft, and others, it’s clear that self-service user-centric mashup, to varying degrees, is a core theme.

BI mashup has such a strong business case that we’re confident it’s more than simply a “down economy” theme. It will almost certainly grow in importance for information and knowledge management professionals as the economy improves.

Self-Service Business Intelligence Depends on Automated Data Discovery

 By James Kobielus

If you tuned into my Forrester teleconference yesterday, you heard me discuss the end-to-end infrastructure necessary to fully support mashup-style self-service business intelligence (BI).

One of the key features for BI mashup is automated source-data discovery, which spares information workers from having to find new data sources or fresh updates from existing sources. Instead, the user simply relies on the BI and back-end data virtualization infrastructure to perform these critical activities as ongoing background tasks. Once new sources and feeds are discovered, transformed to a common semantic model, and published to a BI-mashup registry, all the user needs to do is drag and drop them visually into their mashed-up reports, dashboards, and other analytics.

Automated discovery is not only key to BI mashup, but to trustworthy data as well, because it helps detect and remediate anomalies across disparate data sources. Only a few vendors on the market today provide strong features for automated source discovery. One of them is Composite Software, which recently released an appliance that performs these functions. Another is Exeros, which is the closest thing to an automated-data-discovery pure-play in the market today.

Or, rather, was the closest thing, until IBM announced this morning that it is acquiring Exeros. I’ve been following Exeros for several years and have long considered them a strong candidate for acquisition by a leading BI, data warehousing (DW), data integration (DI), or data quality (DQ) vendor. On IBM’s part, this acquisition makes great sense as a complement to its InfoSphere and Optim portfolios on the data management and governance side of the house.

It will also fit nicely with IBM’s Cognos portfolio as a key enabler, potentially, for BI self-service mashup. As I stated on my teleconference, some vendors are further ahead on putting together a completely mashup-enabling end-to-end BI solution, and Cognos is among them. You can download the teleconference slides from Forrester’s website, listen to my streaming audio, and/or wait for my forthcoming report for more in-depth thoughts on this topic.

Now the ball’s in IBM’s rivals’ courts regarding whether, when, and how they plan to add automated source discovery to their BI portfolios.

Inmon’s Vitriolic Slap At “Virtual Data Warehousing” Does Not Withstand Scrutiny

By James Kobielus

In a recent article, Bill Inmon incinerates a straw man concept that he refers to as “virtual data warehousing (DW).” For those unfamiliar with Inmon, he is generally considered the founder of DW as a data management discipline, has been at it since the 70s, and has more published books and articles to his name than most mortals. So he clearly may be considered an authority on the topic of DW.

But methinks Mr. Inmon doth protest too much on this “virtual DW” bugaboo, however defined (we’ll get to that in a moment). Also, he attacks this concocted notion with such emotional vehemence that it’s clear he considers it a threat to the centralized EDW paradigm upon which he has built his career and reputation.

For starters, his definition of this concept is oddly vague and questionably narrow: “a virtual data warehouse occurs when a query runs around to a lot of databases and does a distributed query.” Essentially, Inmon defines “virtual DW” as the ability to a) farm out a query to be serviced in parallel by two or more distributed databases, b) aggregate and join results from those databases, and c) deliver a unified result set to the requester.

That’s an important query pattern, but not the only one that should be supported under (pick your quasi-synonym) data federation, data virtualization, or enterprise information integration (EII) architectures. Inmon’s definition excludes the many federated queries that may only hit on a single database, with no joins and results aggregation, and with the EII fabric handling the necessary on-demand transformation from that source’s schema to an abstract semantic model.

Per my data federation report from last fall, Forrester has a broader perspective on the topic than does Mr. Inmon. Data federation is any on-demand approach that queries information objects from one or more sources; applies various integration functions to the results; maps the results to a source-agnostic semantic-abstraction model; and delivers the results to requesters. Nothing in the scoping of data federation necessarily requires the multi-source aggregation and joining that Inmon puts at the heart of “virtual DW.”

Putting Inmon’s narrow scoping of “virtual DW” behind us for the moment, let’s consider his chief objections to this approach. First, it requires the “analyst to integrate data” (as if that’s something analysts are ill-suited for or regard as some inordinate burden). Second, it consumes resources, experiences suboptimal performance, and “shuffles a lot of data around the system that otherwise would not need to be moved” (as if centralized DWs don’t consume resources, experience performance bottlenecks, and move data). Third, it is “limited to the [historical] data found in the [source] databases.” Fourth, it suffers from “no reconcilability of data...[hence] no single version of the truth for the corporation.”

It’s a fairly straightforward matter to dispatch these objections:

First, data integration--through ETL, EII, and other approaches--is a core job function for DW professionals, not some alien function outside their core competency.

Second, data federation is often the optimal approach for low-latency BI (just check out the case studies in my data federation and really urgent analytics reports). Federated environments can be tuned to provide top-notch performance and minimize source-system impacts when “shuffling” data around in a decentralized fabric.

Third, the source databases in a federation environment often include DWs, which, per their core function, usually manage a considerable amount of historical data. Once again, see my data federation report with discussion of case studies for a) Federation of Local DWs via Centralized EII Infrastructure and b) Federation of Dispersed EDW and ODS Data Into Siloed BI Environments.

Fourth, data federation is not totally incompatible with data reconciliation. In fact, federation environments can be architected for single version of the truth, data governance, and master data management. However, it can indeed be tricky to manage data quality in federated environments (see Rob Karel’s coverage of MDM and DQ for a deep dive on that issue).

My basic objection to Inmon’s line of discussion is that he treats data federation as mutually exclusive from the enterprise DW (EDW), when in fact they are highly complementary approaches, not just in theory but in real-world deployments. Yes, data federation can be deployed as an alternative to traditional EDWs, providing direct interactive access to online transactional processing (OLTP) data stores. However, data federation can also coexist with, extend, virtualize, and enrich EDWs, as well as other data-persistence nodes such operational data stores (ODS) and online analytical processing (OLAP) data marts. The case studies in the cited reports bear that out.

Inmon’s arguments are worth consideration. The centralized EDW model he touts is useful for illuminating some traditional best practices. But by no means can it do justice to the stubbornly heterogeneous, distributed, mixed-latency BI and DW requirements of most enterprises.

Obama’s Information Agenda....What Is It And Is There A Role For BI?

By James Kobielus

Wow....what a historic week this has been for the United States and the world.

When President Obama and Vice President Biden take office in January, they will have a very full agenda, a rat’s nest of nasty problems to address right off the bat, and a minefield of absurdly high expectations to navigate.

Being an IT industry analyst, I can’t help but wonder where IT fits into the incoming administration’s list of priorities. Indeed, during the campaign, I wasn’t at all sure that any of the candidates had any coherent positions regarding U.S. IT infrastructure, its role in sustaining American competitiveness, or its ability to help the federal government run more efficiently or connect with the constituents. Clearly, the Internet is a bit more stable right now than the financial services sector, so the candidates knew their priorities.

Nevertheless, IT is key to “change we can believe in,” and was instrumental to Obama’s successful campaign. This raises the issue: Does the incoming administration have an Information Agenda, or an IT agenda, and, if so, what might it be? Well, fortunately, a little bit of digging through the Obama campaign’s website has turned up a very thorough set of positions and promises on all things IT.

The most noteworthy promise reads as follows: “Obama will appoint the nation's first Chief Technology Officer (CTO) to ensure that our government and all its agencies have the right infrastructure, policies and services for the 21st century. The CTO will ensure the safety of our networks and will lead an interagency effort, working with chief technology and chief information officers of each of the federal agencies, to ensure that they use best-in-class technologies and share best practices.” I’m not going to opine on whether it makes sense to have a national CTO, though, if Obama makes good on this promise, wouldn’t Al Gore make perfect sense in that role--assuming that a former VP wouldn’t see it as a step down in his political career.

But another Obama promise may prove even more important for the future of American political governance: “Open Up Government to its Citizens:.... An Obama presidency will use cutting-edge technologies to ...creat[e] a new level of transparency, accountability and participation for America's citizens. “ On one level, this suggests an enduring role for BI and performance management technologies in the federal government’s outreach to citizens. What I’m thinking of is some sort of online, continuously refreshed scorecard, dashboard, or report that measures how well the government is serving its constitutents, as measured across many key performance indicators. Or, at the very least, such a scorecard might illustrate how well President Obama is living up to his campaign promises or stacking up against, say, the government’s performance under the outgoing President Bush.

Actually, I’m not entirely sure that an online presidential scorecard would be such a good idea. By its very nature, it would probably be a highly political, partisan, and disputed instrument from the get-go. Judging by the aggressive way in which Obama and the Democrats used the Internet in their campaign, an online presidential scorecard could either become an instrument of ongoing governance or degenerate into a vehicle of perpetual propaganda.

What do you think? Would the U.S. benefit from a national CTO? Would a national online government performance scorecard serve a useful purpose? Would these scorecards, if they established themselves at all levels of government, and as instruments of persuasion in political campaigns, be good or bad for society? And would scorecarding make sense in the political cultures of other nations?

Governance Risk Compliance Agenda....Critical in Turbulent Economy, But Conspicuously Missing from IBM’s IOD Go-To-Market Message

By James Kobielus

If it’s October, it must be time for IBM’s annual Information On Demand (IOD) conference. Initiated 3 years ago, IOD has become an indispensable event for any Information and Knowledge Management (I&KM) professional who has deployed IBM’s sprawling data management solution portfolio.

And IBM doesn’t disappoint: each annual conference is jampacked with important announcements that improve the vendor’s positioning in the forefront of today’s information-driven economy. If anything, IOD has become so crowded with IBM announcements that some important events or themes can easily be overlooked or given less emphasis than they deserve.

IBM realizes this, which is why the vendor works hard in advance of the show to define a coherent set of themes that not only address key customer requirements but also tie to key new product initiatives or releases. This year, that overarching theme is “Information Agenda,” which, you’ll notice, I blogged on several weeks ago. At heart, Information Agenda refers to IBM’s IOD solution focus: positioning its offerings as key customer enablers for business agility, transformation, optimization, and efficiency.

It’s a great theme: very empowering, hopeful, and solution-focused. But, sitting here at IOD, it occurs to me that another key theme is looming in the background, threatening to eclipse it all. The approaching storm is the worldwide financial meltdown, economic slowdown, and the very real likelihood of sharp cuts in IT budgets everywhere. It manifests itself in the increased economic volatility and risk we all face, and for which we’re all trying to hedge all of our strategies and plans. It’s clamping down on us in the increasing government regulation, control, and monitoring being imposed on a growing swath of the world economy. It will result in government-mandated deployment of governance, risk, and compliance (GRC) solutions, which will need to leverage companies’ investments in business intelligence (BI), performance management, and data warehousing (DW) solutions.

Oddly, IBM paid precious little attention to GRC at this year’s IOD--though its Cognos group rolled out  enhancements to its financial performance analytics portfolio,  its enterprise content management (ECM) portfolio enhanced its e-discovery and records management features, and it deepened its already comprehensive Optim portfolio for information lifecycle management (ILM).

And it’s not as if IBM has no GRC strategy. On previous occasions, IBM has put forth a credible strategy that ties its ECM, identity management, and other offerings into a portfolio that is roughly on a function par with Oracle, SAP, and other diversified software vendor.

But not at this year’s IOD. To IBM’s credit, many of their execs discussed the economic climate soberly and insightfully. But nobody, it seemed, wanted to rain on the IOD parade--in which the sunny “business optimization” theme prevailed--by bringing the teeth-gritting GRC theme into it in any way.

My primary beef with Information Agenda? As noted in that previous post, it’s a bit too vague, and a tad too blandly optimistic. Yes, there are always business opportunities, but we’re now in a business landscape where the threats are even more salient.

So, IBM, let’s also discuss customers’ Governance Agendas....their Risk Agendas...their Compliance Agendas...their Demonstrate-to-the-Feds-That-Our-Books-Are-Shipshape Agendas...their Son-of-SarbOx Agendas...their Survive-and-Avoid-Government-Takeover Agendas. How does the IOD portfolio support those agendas?

The big bad recession. Everybody from Ben Bernanke on down says it’s here or coming soon. So why not address it head-on, soberly, with solutions, or, at the very least, approaches that leverage solutions in which customers have already invested?

On a related note, IBM failed to fully address another key concern in a sour economy: cutting IT costs without compromising investments in core BI, analytics, and operational data assets. On the DW appliance side of the equation, IBM did not present a strategic response to recent announcements by Oracle and Teradata, under which those competitors are now providing highly affordable petabyte-scale DW solutions. IBM has strong DW appliance offerings in its InfoSphere Balanced Warehouse portfolio, but it had no new announcements that match Oracle’s and Teradata’s big splashes.

So, if anything, those were the prime disappointments at this year’s IOD show. It was a missed opportunity for IBM both to counter the competition and also address a key concern of its budget- and survival-stressed I&KM customers.

Agenda Politics -- Information Shifts The Balance Of Policy And Influence In Any Organization

By James Kobielus

Yes, like anyone who got a liberal arts degree (me: B.A., Economics), I had to take Political Science 101. And like anyone who sat and thought about what exactly politics is, I soon realized that it's anything but a science. Some call it the "art of the possible," and that strikes me as exactly right.

Or, more to the point, it's the art of engineering consensus and coalition around issues, leading (hopefully) to effective action. Which brings me to the one useful kernel of wisdom that I took away from Poli Sci 101: that the most effective coalition builders are those who engineer a clear, compelling agenda for shaping collective action over the long run. Ironically, Al Gore may have had a greater, lasting impact on the world by losing the 2000 election than if the U.S. Electoral College, Supreme Court, and Floridian perforations had all swung his way. He spearheaded a powerful agenda-based coalition of considerable momentum, focusing the human race on our collective responsibility for global warming. And his chief tool was information: an "inconvenient" but totally science-based truth, reflecting the overwhelming consensus of those who study climate change for a living.

Clearly, no political agenda can succeed in the long run without a potent information agenda -- or, at least, people who are adept at using all available channels to build consensus and spur action. Honestly, when IBM started to use the term "Information Agenda" in their go-to-market messaging, I wasn't sure if I agreed with what they were doing. I understood the notion of, say, a "business optimization," "agility," or "green" agenda, because those terms point (albeit vaguely) to desired results. But information is a tool for building and maintaining an agenda -- it's not an end in its own right.

But then I realized that's not entirely true. Information technology is a precious corporate resource, as are the business intelligence and performance management applications that flow through those channels. So, in that very important sense, an "Information Agenda" makes great sense. Every organization -- public or private sector -- must build and sustain a strong IT, BI, analytics, and performance management capability. Sometimes those assets are wielded for corporate transformation or optimization (by Al Gores of the corporate world). And sometimes -- usually -- they're in the hands of grassroots personnel, who are simply trying to keep their organizations humming smoothly and on an even keel (hopefully, the next U.S.president can keep this big bruised ship of ours from capsizing).

Of course, we all recognize that actionable intelligence is fundamental. Every organization's Information Agenda must revolve around the need to keep that intelligence trustworthy, current, and relevant. So that all decisions -- no matter how humdrum and mundane -- may be grounded solidly in unimpeachable truth.

No matter how inconvenient.

Presidential Campaign Sparks Parallels With Data Governance Challenges

By Rob Karel

For those of us here in the U.S., an extremely important Presidential election is coming in November. For months, Americans have been inundated with spin doctoring and politicking at its worst from both campaigns.  We all hear words like "conservative" and "liberal" used as insults, and rhetoric from both sides say how important it is to foster bipartisan collaboration - while doing everything in their power to alienate those from other political parties.

Putting aside my frustration at seeing nasty politics and posturing to appease the lowest common denominator take precedent over critical debate about issues that truly matter to Americans and our allies, I can't help but marvel at the similarities in politics at the national level to the organizational politics many of us experience on a daily basis within our own companies. More specifically, how the need to adopt data governance to ensure the usefulness and security of critical enterprise data is inhibited by internal politics and posturing.

A brick wall often exists between business and IT where the business must throw their requirements over the wall and 6 months later IT comes back with a technology solution that may or may not actually meet those requirements.  Sometimes the business plays the role of the "bleeding-heart liberal" requesting capabilities and insights that IT feels are unrealistic and undeliverable within a reasonable time and budget. 

In these scenarios, IT is often viewed as  the "inflexible conservative" that sees new requirements as an insult to the existing systems that they have shed blood, sweat, and tears to deliver and this pride of ownership of the current state makes requests for new technology by the business a  threat.   But these roles are often reversed.  At times, IT is the liberal looking to implement cutting edge or next generation technologies (e.g., SOA, MDM) to allow them to better support and scale ever-changing business requirements, but because the conservative business does not have visibility into the precarious state of their IT infrastructure they don't want to finance these improvements because "if it ain't broke, don't fix it!"

When discussing data quality and trustworthiness, the finger-pointing so common in national politics is also standard practice in large enterprises.  The business will often blame IT for data quality issues that they see in their enterprise apps and analytical environments, because the business assumes that if IT is building the pipes, they should also be responsible for the information flowing through those pipes. 

In this case, IT (rightly so, mind you) expresses frustration that only the business should define and measure data quality since the business owns the processes and decisions that are enabled with this data.  This lack of business sponsorship and support is cited as one of the major inhibitors to successful implementation and adoption of ERP, CRM, business intelligence, master data management, and other data-centric IT investments. 

The presidential candidates spin rhetoric such as "bipartisan cooperation is critical" out of one side of their mouths while their campaigns spend more time finding new, creative ways to embarrass their opponents than addresses critical issues.  This same passive aggressive/blatantly aggressive behavior plays out within our corporations too where senior executives say "our data is a critical corporate asset that must be protected" but provides no resources, prioritization, or sponsorship to actually change behaviors and processes that are putting this data at risk in the first place.

While there is little I can do to change the behaviors of our sometimes flawed political process here in the U.S., there are a number of recommendations I can provide to changing the tone of your campaign to improve the quality and usefulness of critical enterprise data.  These include:

• Identifying top-down executive sponsorship early to ensure cross-functional business and IT participation is mandatory, not voluntary.
• Limiting initial scope of your data governance program to addressing only the data that supports the business processes most critical to your company, and to those business stakeholders most willing and able to articulate how poor data quality is impacting those processes.
• Staffing business and IT stewards with business analysts that can effectively translate business requirements into technology solutions.  These individuals are the bridge that must ensure business and IT collaboration.  See The New Business Analyst for more on the business analyst role.
• Developing a compelling business case that can quantitatively measure the benefits of investing in data quality and governance. See A Truism For Trusted Data: Think Big, Start Small for best practices in developing a bottom-up valuation approach as well as Building The Business Case For Master Data Management for help in aligning your trusted data initiative with your company's strategic priorities.

In the meantime, I'll look forward to seeing everyone at the polls on November 4th!