Inside the Biz with Jill Dyche

Master Data Quality and Governance Q&A

In which Jill tackles questions from some of the 1172 registrants of last week’s TDWI SuperWebinar. (Did she mention there were 1172 registrants?)

Last week’s TDWI Master Data Quality and Governance SuperWebinar represented an on-line reprise of the live conference—co-chaired by yours truly and TDWI Sr. Research Manager Philip Russom—this past April in Savannah. Obviously the on-line format doesn’t lend itself to one-on-one sessions or audience Q&As of the live event. So, herewith I’m taking a stab at some of the on-line questions submitted from webcast attendees.

Donna: Our IT group cannot seem to get energy behind ownership of the IT role in governance and IT data and metadata. What can I do to stimulate the IT side of governance?

Jill: Okay, Donna, I sense from your question that the business is pushing data governance at your company and IT is reluctant to jump on board.  So I’m going to give you a working answer and a cynical answer. You choose which one’s most apt for where you work.

The working answer is that the business should engage the highest levels of IT—probably the CIO—and explain the problem(s) that launching a data governance effort promises to solve. Remember in my keynote I discussed putting executives in the position of saying “no”? That goes for IT executives, too. Woe to the CIO who breaks the news to beleaguered business leaders that IT can’t deliver.

Here’s the cynical answer: Invite Talend, Initiate (IBM), and Kalido (the esteemed sponsors of our SuperWebinar) to brief you about their data management solutions. Invite IT management to the briefings. Once you’ve been briefed explain to IT that as the business launches data governance it will likely acquire data governance enabling solutions as well. IT gets itchy when the business acquires its own technologies. This might get them to the table faster than you can say, “data as a service!”

Satish: Do you keep the bad history data after you clean up the data in your master hub?

Jill: Several of our clients do indeed hang on to the bad records resulting from their MDM matching. For instance your hub might deem three different customer records to be the same person, and it might earmark a specific record as the best one. Retaining the other records will give you an audit trail and let you refine business rules so you understand what the determining factors are in match selection. It will also let you measure improvements in your data as survivorship issues become clear and fewer anomalies emerge. (I’m assuming you’re talking about keeping a history of non-surviving master records, and not historical data, like you’d put in a data warehouse.)

Vicki: Any tactical advice on how to start implementation of data governance?

Jill: Beyond my webinar admonishments to pinpoint a business problem first? Not really, Vicki. We’re already seeing the fallout from companies that haven’t linked data governance to a business problem, and it ain’t pretty. But let’s assume your challenge is more about data management than data governance, and you need to formalize some practices around data quality, cleansing, validation, standardization, and matching. Let’s say that’s the issue, ‘kay?

I still say pinpoint a business problem first. This is because as you do your discovery, you’ll see how bad things really are. IT doesn’t have a bona-fide data correction process, do they Vicki? People are manually reconciling records all over the place, aren’t they? There’s no metadata (that anyone knows about, anyway) and there are pockets of data modeling going on in different departments. Your company is over-investing in effort, Vicki. Quantify how much what I call these “campfire” work efforts are really costing, then pitch data management as a foundation for data governance.

But still link it to a business problem.

Chris: I’m a Data Architect responsible for creating a Data Management Program. One thing I have been challenged with is developing ROI. Any ideas or experiences you have seen in creating ROI around such a program?

Jill: Chris, did you read my response to Vicki? Quantify some of the costs associated with campfire data management. You won’t be able to quantify them all, but find some juicy ones. Like the fact that your finance department is making over 175,000 adjustments per month before it closes the books. And even then it has to explain to regulators why the books say what they say after they’re closed. And in the dark of night, someone in finance knows the books shouldn’t have been closed, and he’s got night sweats. (Okay, that last part doesn’t have a quantifiable cost, but I think it drove the point home in a dramatic way, don’t you?)

Anyway, once you’ve quantified the human labor costs of not having formal data management, whip that up into a presentation with some hard-hitting calculations and call the CFO. He’ll take the meeting and fund your Data Management Program. He might even buy you lunch—as long as it meets corporate expense guidelines.

Wendy: Who is best charged with building and writing data governance policies?

Jill: You are, Wendy. Because you’re the only person in your group that’s smart enough to have asked that question. So by default, it’s gotta be you.

Seriously, crafting policies on behalf of enterprise data is the job of the data governance council or board.  I’m going to defer the policy question to Marty Moseley, who wrote a great blog post on it a while ago. Read it here.

Arun: Hi—I’m a solution architect for DW/BI and would like to know the basic hierarchical structure of a Data Governance Board?

Jill: Hi Arun! Craft an org chart and put yourself at the top and see if anyone notices. This tactic has been effective throughout history. I say give it a whirl.

If you don’t have the intestinal fortitude then I have to tell you that the makeup of your data governance board will likely change over time as new business strategies and priorities emerge and executives become tasked with overseeing them, and the information that enables them. So to answer your question, there’s really no fixed hierarchy. Having said that, the person initially in charge of your data governance council has a lot to do with the council’s perceived credibility. So assuming you yourself demur from donning the mantle [editorial comment: DO IT, Arun! DO IT!] then make sure that the council chair has the organizational authority to make governance stick.

The Importance of Scope in Data Quality Efforts

This post was originally featured on www.smartdatacollective.com

When it comes to data quality, I fervently believe that it is destined for widespread adoption. As a concept data quality has been around for a while, but until now it’s only truly been appreciated by a group of aficionados.  But just like taco trucks, the HBO show “In Treatment,” video on demand, and Adam Lambert, data quality’s best days are actually ahead of it.

Part of the reason data quality hasn’t yet hit its stride is because it remains a difficult sell. Those of us in the business intelligence and data integration communities understand that accurate and meaningful data is a business issue. And well-intentioned though they may be, IT people have gone about making the pitch the wrong way.

We—vendors,  consultants, and practitioners in the IT community—blather on about data quality being a business issue and requiring a business case and a repeatable set of processes but at the end of the day automation remains the center of most data quality discussions. As we try to explain the ROI of name and address correction, deterministic matching, multi-source data profiling, and the pros and cons of the cloud, business executives are thinking two things:

1. “Jeezus I’m bored.”
2. “I wonder how we would start something like this? Where would we begin?”

In fact the topic of scope is a huge gaping hole in the data quality conversation. As I work with clients on setting up data governance, we often use the bad reputation of corporate data as its pretext. We always, always talk about the boundaries of the initial data quality effort. Unless you can circumscribe the scope of data quality, you can’t quantify its value.

In our experience, there are 5 levels of data quality delivery that can quickly establish not only the scope of an initial data quality effort, but also the actual duties and resources involved in the initial project:

(Click Diagram to Enlarge.)

By specifying the initial scope of the data to be corrected we’re establishing the boundaries of the effort itself. We’re also more likely to be solving a real-life problem. Thus we make the initial win much more impactful, thus securing stakeholder participation. Moreover, where we start our data quality effort is not necessarily where we’ll finish, so we can ensure an incremental approach to setting up the program and its roles.

Business executives and users can consume a well-scoped problem, especially if it makes their jobs easy or propels progress. And if we solve it in a way that benefits the business—eliminating risk, ensuring economies of scale, and driving revenues—we might even get budget for a data quality tool!

Zen and Mao

In which Jill considers spending less, but buying smart.

Lately I’ve become aware—okay, it’s been brought to my attention—that I buy stuff I don’t need. My two big weaknesses are Costco and art fairs.

When it comes to Costco, I don’t really need half-gallon can of 3-bean salad, a foam rubber kitchen rug, or a bag of those fabulous dark chocolate-covered Açai berries. I just sort of situationally covet them. Plus the shopping carts at Costco are huge and a 32 ounce bag of Kirkland Cashew Clusters with Almonds and Pumpkin seeds seems a paltry—though highly recommended!—bounty. Do I really need a vat of protein powder? No. The waterproof outdoor chair cushions? No. The double-size pack of Strivectin stretch mark cream? Maybe I do, maybe I don’t, mind your own business.

As far as art fairs go, a few weeks ago I wandered through an open-air festival and discovered a woman selling Asian-inspired jewelry. I noticed a large pin featuring the face of the Buddha. If I wore that to internal status meetings, I thought, it could inspire Zen-like behavior. After all, I couldn’t very well lug my Buddha garden statue (thanks, Costco!) with me everywhere I went, could I? So I bought the Buddha pin and wore it the following week to a client meeting.

“Gone Commie on us, Dyché?” asked my slapstick-humored CIO client examining my new lapel pin. It was only then that I noticed that the countenance peering serenely from my lapel looked a lot more like the Chairman Mao than the Buddha. When it comes to adorning my clothing—all due respect—Chairman Mao wouldn’t be my first choice. So much for the Zen.

This all reminds me of how my clients have been spending their IT budgets—or not spending them. A bank engaged us last year to assess its aging data warehouse and suggest a subsequent plan of attack. Based on existing cost and resource challenges, we recommended a wholesale re-platforming. We gathered requirements, performed an ROI analysis, and wrote a vendor RFP for the client. The subsequent investment in the new data warehouse was $7 million, an investment that the bank should recoup in the next four years.

The bank was thoughtful and practical about our recommendations. IT management didn’t futz around. But when it came to our recommendation to invest in a data quality tool and start a project they were positively inert. Never mind that solution we recommended would be a fraction of the price of the new data warehouse platform. “It’s easier for us to justify a $7 million capital expenditure than it is to justify a new piece of software,” they apologized.

Which brings me back to my Buddha pin. I thought that it might do something for me that it ultimately didn’t do. Looking back on that purchase it was an over-investment. Some might even call it a waste of money.

The dark chocolate covered Açai berries are a totally different story, though. [Chomp, chomp.] With that, I wish you Namaste.

photo by kevindooly via Flickr (Creative Commons license)

My Regression Theory

In which Jill confirms that everyone who runs backwards does so awkwardly.

It’s a familiar story. An executive at a Fortune 1000 company leaves to start his own business. The market craters, his business falters, and he returns hat in hand to his old firm and resumes his old job. This just happened to a client of mine, a brilliant marketing guy who tried to launch a consulting firm just as companies were cutting back. He re-joined his former employer, a specialty retailer, and took up where he left off. We caught up over drinks a few weeks ago and I asked him what had changed between his departure and his return.

“Everything,” he said with a deadpan look on his face. I couldn’t tell whether this was good news or bad news. Knowing his planning skills, I was hoping that during his absence the retailer had taken his vision of smaller customer segments and multi-channel inbound and outbound outreach and executed on it, and was now celebrating explosive profitability and jaw-dropping sales uplift.

But that wasn’t what he meant. In fact, my friend explained, his company had regressed since he’d left. The CRM system he’d acquired in his position as Executive Vice President of Customer Marketing had been decommissioned. The team he built had scattered across departments and regions, and to competitors. Membership in the retailer’s loyalty program had shrunk, as had the percentage of return shoppers and the number of items in their market baskets. Everything had changed alright.

“It’s as if I’d never worked here,” my friend lamented. “I’m starting back at square one. Only this time I have a smaller budget than before and fewer direct reports.” He took a forlorn swig of his single-malt as we discussed what it would take to get him back on track.

It’s true that in a down economy laggard and leaderless companies stagnate. They delay key projects, instead hunkering down while awaiting the salvation of an economic rebound. Fear and paranoia—and not the Andy Grove kind—rule the day. Backbiting and land grabs are the rule.

But it’s even worse than that. I’ve seen multiple instances lately of companies actually regressing. I’ve watched as unqualified managers slash and burn successful efforts, shedding sound plans and disbanding high performing teams. At best, these managers don’t know what to do, so instead they un-do, unaware of the consequences. At worst, rampant opportunism and leadership gaps invite empire building or plays for projects that they are ill-equipped to propel forward. Determined to leave their mark, they thwart progress.  Forget creative destruction. This is destructive destruction writ large on viable business initiatives at companies far and wide.

The glimmer of hope is that there is talent waiting in the wings to get these companies moving in the right direction—provided their leadership can handle the newfound momentum. This talent can come from consultants (who are often engaged to drive both the slashing and the rebuilding), new hires, and even those exiles that you lost once upon a time. The companies that actually pick up the pace are those that see the opportunity before their competitors do, and grab the talent before the economy gets humming again.

Not to put too fine a point on it, but that means now.

Photo by Mykl Roventine via Flickr (Creative Commons License)

Social Media Strategy Q & A

In which Jill conducts a Q&A—and she’s not even doing a podcast!!!

I got some great feedback on my last blog post, The 4 Es of Social Media Strategy, and some interesting questions. In fact the back-and-forth was so cool that I thought I’d share some of it in this post. Since many of you e-mailed me your feedback instead of posting comments—why, oh why??—I’ll use only first names here.

Question:

I liked your examples of how Levi and JC Penney are leveraging social media. But how does this start? Do people just get in a room and decide to create social communities for their companies? I can’t get my executives off of vision statements much less convince them we need a Facebook page for our company! Can we start small?

Answer:

Drivers of social media can be global—meaning that there is widespread consensus across the company about the goals for social media and the new behaviors it will enable. Or it can be “local,” exclusive to one line of business or working group. In fact, in my experience the most effective social media initiatives are decidedly not global but focus on the objectives of a single department or brand. Look at Del Monte’s “I Love My Dog” campaign for its pet foods brands.

For a more global approach look at the work of Scott Monty, the head of social media for Ford Motor Company, who polishes his company’s brand every day.

Question:

I read your blog for your observations on BI, CRM, and data integration. Why are you blogging about social media so much these days?

Answer:

‘Cuz I have a blog and I’m not afraid to use it! Seriously, I’m writing more about social media because my clients are talking more about it. And if you really think about it, analytics, data integration, CRM, and social media are really of a piece: they should work together to enhance our understanding of our customers’ behaviors and preferences.

Question:

I really like your 4 Es. Is there an order to them?

Answer (in 2 parts):

Part 1: No order. It really depends on your business priorities, your branding strategy, what you want from your customers, and the whether there’s an implied quid pro quo to participate in your on-line communities.

Part 2: Make that FIVE Es of Social Media Strategy! This is courtesy of my friend Phil Simon, who rightly suggested a 5th E: Evaluation.

Phil’s point was that measurement of social media success is fairly straightforward, so you should plan on a regular way of assessing whether Expose, Engage, Entertain, and Educate are really working. Hence, the “E” for Evaluate.

The 4 Es of Social Media Strategy

In which Jill dons the chapeau of Reluctant Social Media Strategist and shares lessons learned.

The conversation goes like this:

Client: “We need to analyze our social media data.”

Me: “Cool. What’s the desired outcome?”

Client: “We need to get active with social media.”

Me: “Yes. But what’s the need, pain, or problem?”

Client: We need to analyze our social media data.”

Discussions like this happen in business all the time, and they’re not exclusive to the topic of social media. But show me a company that’s vague about the drivers for a new initiative and I’ll show you a company that doesn’t have a solid strategy in place. And that goes for social media, too.

As our clients engage with us more and more on social media analytics, we’re noticing that there’s a natural progression of maturity. We’re also doing more coaching around social media strategy to drive related data strategy and governance efforts. Apart from the usual platitudes of “getting closer to employees, partners, and customers via lower-cost channels” it turns out very few business leaders can answer my question about the desired outcome of social media analytics.

In our experience, there needs to be at least one prevalent driver for social media. I call these the “4 Es of Social Media Strategy.” They are:

There are already some great examples of companies that have zeroed in on one of these areas used it as a foundation for other drivers. For instance, JC Penney offers its Facebook fans—now over half a million strong—unique deals and discounts, clearly leveraging the social media channel to Engage a younger demographic of apparel customers. Earlier this year the retailer leaked its Oscar ads on Facebook before the show aired, mixing a little Entertain with a lot of Expose.

Indeed, many on-line retailers remind shoppers about shipping rates and return policies on their websites and through their blogs. But web strategist Jeremiah Owyang wrote this week about how Levi uses social media to Educate shoppers to “like” a product and to tell their friends about it.

Del Monte has leveraged the power of social networking with its “I Love My Dog” community, in which dog lovers can interact with the company and with each other. Del Monte gets 40 percent of its revenues through pet products (Snausages, anyone?). Who knew?

And that’s the point. Del Monte has gone from Expose as its primary driver—ensuring that pet owners ($2 billion a year strong) know about its various brands—and moved to Engage as its workaday model. The packaged goods company enlists its ready-made social community in surveys—using it to test marketing campaigns and get feedback on new product ideas—and occasionally moving over to Educate when it comes to product ingredients. In the meantime Del Monte is collecting information that can inform new campaigns and product ideas.

Over time your company’s social media strategy can incorporate each of the 4 Es, but there is usually a single prevailing need that will likely justify the initial effort, and provide the foundational platform and skill sets for subsequent social media activities. The key is to avoid making social media a “research project” or, as a Chief Marketing Officer pronounced it recently, “an intellectual exercise with no tangible benefits.” In a word, Ouch!

Image by webtreats via Flickr.

The Tyranny of Consensus

In which Jill questions authority, and authority runs screaming.

Baseball legend Satchel Paige once said that “None of us is as smart as all of us.” As a management consultant I’ve learned that there’s a big difference between widespread consensus and the appearance of widespread consensus. Inexperienced or conflict-averse leaders (the latter is an oxymoron) stop short of doing the legwork to engage and educate their constituents. Instead they try instilling the often-false belief that “everyone else is onboard, and you should be too.”

It’s surprising how many people actually cede to the tyranny of consensus. They rationalize their decisions in unexpected ways, blaming corporate politics, industry best practices, the lack of decision rights in their organizations, or quirky corporate cultures. They cave. Psychologists call people like this “cognitive misers.” They place the shortcuts of established thinking and entrenched behaviors over deliberate analysis.

My firm is often hired by people who—whether they own the term or not—are change agents. They see the promise of unraveling established paradigms and instilling new ones. They aren’t afraid to deconstruct scenarios, build use cases, map decision trees, or find stakeholders who aren’t afraid to ask difficult questions. Ask such leaders the question, “Is this the hill you want to die on?” and they’ll answer, “Good as any.”

When such leaders are effective their colleagues embrace their new ideas and are willing to test them out. But when they underestimate the incumbent power structure (or the degree of entropy) they’re dismissed as uninformed or, worse, just wrong.

It’s the wisdom of crowds turned upside down. Two or more people making a decision doesn’t mean that decision is the right one. Blame it on the path of least resistance. Blame it on the bad economy. But really, blame it on leaders who are unwilling to push their followers to consider new ways of doing things, reward innovation, and upset the status quo.

Think about this in terms of your data quality, master data, BI-rejuvenation, or center of excellence opportunity, and ask yourself two questions: If not now, when? And if not you, who?

The Next Wave of Technologies

In which Jill knees new technologies in the groin and watches as they rally in spite of it all.

When Phil Simon asked me to write the Foreword to his new book, The Next Wave of Technologies: Opportunities in Chaos, I wasn’t sure it would be my cup of tea. After all, did we really want to proselytize the view that new technologies would beget chaos? Our existing technologies do a nice job of that already, thank you very much. So I read the book. Then I said yes.

I said yes because I thought the topics were provocative. In addition to Phil’s own chapters, which focus on how technology can set companies apart, his contributors have established the standards for their respective topics. Amy Wohl has written the definitive summary of Software as a Service (SaaS) solutions (Chapter 6); Dalton Cervo does a thorough survey on Master Data Management (MDM)—making the hard-won case that MDM is indeed a business solution (Chapter 12);  Jay Miletsky provides a great analysis of both the benefits and risks of the use of social media (Chapter 9); and Michael Krigsman explains that, even as we learn how to adopt these new solutions, there are nevertheless also new ways to fail (Chapter 18).

Notwithstanding other chapters on sustainability, agile development, the mobile enterprise, and open source, Phil’s book is far from a compendium of technology breakthroughs courtesy of the last decade. Interwoven throughout this tapestry of technology is the golden thread of business value. Implicit in each chapter is the assumption that technology-in-a-vacuum is a bust. There must be business problems that these solutions can fix.

In my Foreword I resurrect the now well-worn argument, initially posed by Harvard Business Review editor Nicholas Carr, that IT doesn’t matter. I poke the argument, slap it around a little, then give it a swift upper cut. (Read the book to see if the argument bounces back.) In short Phil Simon’s book is about the application of each individual solution to real-life and often-urgent business problems. It’s about reclaiming control of your supply chain, financial systems, or innovations through Enterprise Risk Management. It’s about social media yielding improvements in collaboration and saving companies development time (and money). It’s about store employees using mobile dashboards so they can spend less time behind the register and more time with customers.

It’s about—as Tushar Hazra says in his insightful chapter on SOA—“detangling complicated, coupled…interdependent applications.” Maybe this can all be done by well-meaning IT professionals with a common set of objectives. Maybe in can be done by autodidacts on the business side. Maybe it can be done with the next wave of technologies. And maybe the whole is greater than the sum of its parts.

Understanding Social Personas

In which Jill reveals her secret. (Okay, one of her secrets.)

There are some things that only a few good friends know about me. For instance, I like running on the beach. I watch Animal Planet religiously. I enjoy napping in the back of the station wagon, even when it’s parked in the garage. And—I’m not proud of this, but here it goes—on occasion I eat my own poop. The secret is this:  I’m really a dog. And I have 800 Twitter followers.

Don’t go looking for these factoids at www.twitter.com/jilldyche. That’s someone else. Or IS it?

You see, when I started using Twitter I had to reconcile different areas of my life. I like to tweet about professional stuff, including customer relationship management (CRM), social media, and information as a strategic enabler. I also like to chat and share info with my non-work friends, many of whom are hiking buddies, dog rescue advocates, or fellow charity volunteers. Sometimes my work tweeps aren’t necessarily aligned with all my goodwill activities, nor do they always care about my doggie sagas. (Amy is blind, Lu is 14 with vestibular disease, and Colby has epilepsy.)  Likewise my non-work buddies think MDM is simply the acronym for the new slogan, “Mutt Dogs Matter!”

Since Colby comes the closest of my three dogs to having opposable thumbs, I set her up on Twitter. And thus I adopted a new social persona that lets me communicate with a subset of my friends in a more meaningful way, without bothering the rest with humdrum observations or irrelevant news.

[Hiking and dog buddies: go ahead and skip the following paragraph.]

Sound familiar? The definition of CRM (Customer Relationship Management) is the ability to differentiate customers in order to distinguish their treatment. That applies to our sales force, our customer service reps, and yes, to marketing. Why e-mail a customer a discount code for a product he already has? Why ship a catalog aimed at newly-marrieds to a single grandmother? Why pitch cat food to… You get the idea.

Your social persona means more than just having the answer to “Which Superhero are you?” or “Which Barbie are you?” (No, I’m not kidding.) It represents a circumscribed collection of behaviors and preferences, not necessarily your entire set of behaviors and preferences. Social personas—alright work friends, personae—encompass similar attributes and are more narrowly defined. Our social personas help us refine our networks, participate in new on-line communities, and invite fresh collaborations. Social personas essentially allow customers to segment themselves. And they’ll segment themselves in a far more accurate and nuanced way than a marketing department ever could. The implications on sales uplift and return on marketing investment could be staggering.

Indeed some savvy companies have discovered Colby, and are pitching her products according to who she is and what she, er, says. Colby buys bully sticks from Value Pet Supplies (@valuepet); attends fundraisers on behalf of Best Friends Animal Sanctuary (@BFAS); browses the aisles of Red Barn (@redbarnfeed); and has even been known to watch Vet TV (@veterinarytelevision). Colby is a Coonhound, but she’s also a consumer. Those with a stake in the $45 billion pet care industry are cultivating relationships with her.

[Hikers and dog friends: go straight to the end.]

This adds a new wrinkle to social CRM, especially to the already challenging practice of customer segmentation. Most companies still struggle to transcend the well-worn practice of demographic segmentation, seeking to enrich and integrate their customer data to enable more sophisticated behavioral, preference, and usage-based segmentation and with them more intelligent ways to engage and interact with customers and prospects. Persona-based segmentation should be next on their lists.

The hard part of social personas, of course, is establishing the connections between social identities. The very hard part is collecting and structuring that data, then integrating it with the rest of the customer’s profile in a sustainable way.  One could argue that companies have yet to accomplish this successfully with their on-premise structured data, never mind social media data.  But the time to start planning is now.

Among Colby’s followers are @BuckBasset, @Otis_the_Pug, @WinterKitten, and Governor Arnold Schwarzenneger (@Schwarzenegger). You can follow Colby on Twitter at www.twitter.com/Colby_the_Dog. She’ll follow you back just as soon as she finishes her bully stick.

Charm School: It’s Not Just for IT Anymore

In which Jill reminds the business that it’s their business, too.

In 2008 Business Week reported that Kimberly-Clark had run a charm school for its pared-down IT workforce. The consumer packaged goods giant had recently outsourced almost 80 percent of its technology staff, and there were high expectations for the survivors. Improving communications with the business constituency was a priority. Hence the techie finishing school.

There’s a great Dilbert cartoon in which Dilbert asks a user for his business requirements. The user suggest that instead Dilbert just build the system, “and then I’ll tell your boss that it doesn’t meet my needs.” Welcome to a new era of shared accountability where the business is—or at least, should be—as much on the hook for IT project success as IT is.

As we’ve formalized business requirements gathering processes and even adopted new tools to help us automate them, business users can no longer simply finger-wag at IT. They’ve got skin in the game, too. As much as they’d prefer to call someone to run some numbers, or rattle of a wish list in a status meeting, business stakeholders need formal rules of engagement just as much as their IT brethren. Likewise, IT managers can’t simply rely on the overblown promises of iterative prototyping to draw users in, or depend on their trusty enterprise app vendor to prescribe a solution in a vacuum. Mutual accountability is the new black.

The diagram below illustrates an example of a sustained hand-off cycle between IT and the business at one of our clients:

In essence, this was the unified gameplan that had been missing. In this new world, the business can’t enlist IT until they’ve done their own homework. This means thoroughly defining the initiative—here, ensuring that it’s aligned to strategy and a complete business case is developed—before engaging IT and entering the development pipeline. Note that each of the numbered steps represents its own process or set of processes. (IT people will enjoy the divine justice that there are more steps on the business side.)

Business stakeholders need to not only adopt their own processes for defining and justifying initiatives, but they have to articulate their expectations clearly and stay actively involved in delivery. The days of the IT-business mind-meld when technology staff relied on gut-feel, personal relationships, and so much storytelling to arrive at the right technology solution are over. So are the days of what blogger Xavier Noemann calls the “Kramden-esque hamana hamana” of user-speak. The fact is business users have to step up, articulate their desired outcomes, and work with IT. And maybe they can start being nicer to each other, charm school be damned!

photo by Bogdix via Flickr (Creative Commons License)