About

I'm a partner in the advanced analytics group at Bain & Company, the global management consulting firm. My primary focus is on marketing analytics (bio). I've been writing here (views my own) about marketing, technology, e-business, and analytics since 2003 (blog name explained).

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June 16, 2013

Organizing for #Analytics - Seven Considerations

We're now in the blood-sugar-crash phase of the Analytics / Big Data hype cycle, where the gap between promise and reality is greatest.  Presenting symptoms of the gap include complaints about alignment, access to data, capacity to act on data-driven insights, and talent.  This September 2012 HBR blog post by Paul Barth and Randy Bean of NewVantage Partners underscores this with some interesting data.

Executives' anxiety about this gap is also at its peak.  Many of them turn to organization as their prime lever for solving things. A question I get a lot is "How should we organize our analytic capabilities?"  Related ones include "How centralized should they be?", and "What should be on the business side, and what belongs in IT?"  

This post suggests a few criteria for helping to answer these questions.  But first, I'd like to offer a principle for tackling this generally:

Think organization last, not first.

A corollary to this might be, "Role is as role does."  Too much attention today is paid to developing and organizing for analytic capability.  Not enough attention is paid to defining and managing a portfolio of important business opportunities that leverage this capability.  In our work with clients, we focus on building capability through practice and results.  Our litmus test for whether we're making progress is a rule we call "3-2-1": In each quarter, the portfolio of business opportunities we're supporting with analytic efforts has to yield at least three "news you can use" insights, two experiments based on these insights, and one "scaling" of prior experiments to "production", with commensurate results.  (The specific goals we set for each of these varies of course from situation to situation, but the approach is the same.)

Approaching things this way has several benefits:

  • You frame "Analytics" and "Big Data" requirements in terms of what you need to solve specific challenges relevant to you, not in terms of a vendor's list of features;
  • You stay focused on the result, and not the input, so you don't invest past the point of diminishing returns;
  • By keeping cycles short and accountable to this rule, you hedge execution risk and maximize learning;
  • Your talent recruitment, development, and organization are done in the context of explicit opportunities, and thus stay flexible and integrated around concrete business results and not abstract concepts for what you need;
  • The results-oriented management of the capability helps build confidence that the overall ROI expected will be achieved.  Momentum is strategic.

Now, two critiques that can be made of this approach are, first, that it's too ad hoc and therefore misses opportunities to leverage experience beyond each individual opportunity addressed, and second, that it ignores that most people are "tribal" and that their behaviors are shaped accordingly.  So once you've got a decent portfolio assembled and you're managing it along, here are some organizational considerations you can apply to help decide where folks should "live":

  • For the business opportunities you're faced with, how unique is "local knowledge" -- that is, intimate knowledge of the specific market dynamics or operational mechanics that generate the data and shape the necessary analytics -- to each of them?  The more so, the more it will make sense to place your analysts in the groups responsible for those areas.
  • To what extent does the type of analysis you are pursuing require a certain degree of critical mass? It's hard for a single person or even small groups to manage and mine a Big Data capability, and if you sprinkle Big Data analysts throughout your firm to support different groups, you overwhelm each of them and under-serve the opportunity. Plus, each of them ends up with different Hammers Looking For Nails based on the particular tools and techniques they learn, rather than picking the best ones for different jobs.
  • How important is enterprise leverage to the business case for your capability?  If it is, centralizing your analysts so that purchasing efficiencies and idea sharing and reuse are maximized will be more important.
  • Are you concerned about objectivity?  When analysts get embedded deeply with business teams, there's a risk they can "go native", either because they fall in love with the solutions they're part of developing, or because of pressure, subtle and otherwise, to prove these solutions work.  This phenomenon is well-documented in scientific fields, even with peer review, so it's certainly more problematic in business.  
  • Are you, for whatever reason, having trouble keeping your analysts and their efforts aligned with your key priorities? For example, if one group needs to quickly get a product into market to grab its share of a high-growth opportunity, and then evolve it from there, and your analysts work in a group whose norms and objectives are more about "perfect" than "good enough", you may need to move folks, or get different folks in place.
  • How's your analyst-marketer relationship? If they're talking and working together productively, and the interpersonal karma is good, you can worry less about whether their boxes on the chart are closer or further apart.
  • Finally, which of these four "C's" describes the behavior you're trying to encourage: communication, coordination, collaboration, or control?  At the communication end of the spectrum, you just want folks to be aware of each other's efforts.  Coordination, for example, can mean "Hey, I'll be running my test Tuesday, so could you wait until Wednesday?"  Collaboration may require formal re-grouping, but it might only be temporary.  Control can be necessary for effective execution of complex projects.  The more analytic success relies on such control, rather than being satisfied by the "lesser" C's, the more you may solve for that with organization.

In our work we'll typically apply these criteria using scoresheets to evaluate either or both the specific business challenges we're solving for or the organizational models we're evaluating as possible options.  Sometimes we just use "high-medium-low" assessments, and other times we'll do the math to help us stay objective about different ways to go.  The main things are to keep attention to organization in balance with attention to progress, and to keep discussions about organization focused on the needs of the business, rather than allowing them to devolve into proxy battles for executive power and influence.

June 12, 2013

Privacy vs. Security Survey Interim Results #prism #analytics

This week, one of the big news items is the disclosure of the NSA's Prism program that collects all sorts of our electronic communications, to help identify terrorists and prevent attacks.

I was struck by three things.  One is the recency bias in the outrage expressed by many people.  Not sixty days ago we were all horrified at the news of the Boston Marathon bombings.  Another is the polarization of the debate.  Consider the contrast the Hullabaloo blog draws between "insurrectionists" and "institutionalists".  The third was the superficial treatment of the tradeoffs folks would be willing to make.  Yesterday the New York Times Caucus blog published the results of a survey that suggested most folks are fence-sitters on the tradeoff between privacy and security, but left it more or less at that.  (The Onion wasn't far behind with a perfect send-up of the ambivalence we feel.)

In sum, biased decision-making based on excessively simplified choices using limited data.  Not helpful. Better would be a more nuanced examination of the tradeoff between the privacy you would be willing to give up for the potential lives saved.  I see this opportunity to improve decision making alot, and I thought this would be an interesting example to illustrate how framing and informing an issue differently can help.  So I posted this survey: https://t.co/et0Bs0OrKF

Here are some early results from twelve folks who kindly took it (please feel free to add your answers, if I get enough more I'll update the results):

Privacy vs security

(Each axis is a seven point scale, 1 at lowest and 7 at highest.  Bubble size = # of respondents who provided that tradeoff as their answer.  No bubble / just label = 1 respondent, biggest bubble at lower right = 3 respondents.)

Interesting distribution, tending slightly toward folks valuing (their own) privacy over (other people's) security.

Now my friend and business school classmate Sam Kinney suggested this tradeoff was a false choice.  I disagreed with him. But the exchange did get me to think a bit further.  More data isn't necessarily linear in its benefits.  It could have diminishing returns of course (as I argued in Pragmalytics) but it could also have increasing value as the incremental data might fill in a puzzle or help to make a connection.  While that relationship between data and safety is hard for me to process, the government might help its case by being less deceptive and more transparent about what it's collecting, and its relative benefits.  It might do this, if not for principle, then for the practical value of controlling the terms of the debate when, as David Brooks wrote so brilliantly this week, an increasingly anomic society cultivates Edward Snowdens at an accelerating clip.

I'm skeptical about the value of this data for identifying terrorists and preventing their attacks.  Any competent terrorist network will use burner phones, run its own email servers, and communicate in code.  But maybe the data surveillance program has value because it raises the bar to this level of infrastructure and process, and thus makes it harder for such networks to operate.

I'm not concerned about the use of my data for security purposes, especially not if it can save innocent boys and girls from losing limbs at the hands of sick whackos.  I am really concerned it might get reused for other purposes in ways I don't approve, or by folks whose motives I don't approve, so I'm sure we could improve oversight, not only for what data gets used how, but of the vast, outsourced, increasingly unaccountable government we have in place. But right now, against the broader backdrop of gridlock on essentially any important public issue, I just think the debate needs to get more utilitarian, and less political and ideological.  And, I think analytically-inclined folks can play a productive role in making this happen.

(Thanks to @zimbalist and @perryhewitt for steering me to some great links, and to Sam for pushing my thinking.)

May 20, 2013

"How to Engage Consumers in a Multi-Platform World?" See you May 22 @APPNATION bootcamp panel in NYC

Sponsorpay's Global Sales SVP Andy Bibby kindly asked me to join his NYC Internet Week APPNATION panel on Wednesday, May 22 2:15-3p at 82 Mercer.  Hope to see you there, watch this space for a recap of the conversation.

May 19, 2013

@nathanheller #MOOCs in The New Yorker: You Don't Need A Weatherman

The May 20th 2013 edition of The New Yorker has an article by Vogue writer Nathan Heller on Massive Online Open Courses (MOOCs) titled "Laptop U: Has the future of college moved online?"  The author explores, or at least raises, a number of related questions.  How (well) does the traditional offline learning experience transfer online?  Is the online learning experience more or less effective than the traditional one? (By what standard? For what material?  What is gained and lost?)  What will MOOCs mean for different colleges and universities, and their faculties?  How will the MOOC revolution be funded?  (In particular, what revenue model will emerge?)

Having worked a lot in the sector, for both public and private university clients, developing everything from technology, to online-enabled programs themselves, to analytic approaches, and even on marketing and promotion, the article was a good prompt for me to try to boil out some ways to think about answering these questions.

The article focuses almost exclusively on Harvard and EdX, the 12-school joint venture through which it's pursuing MOOCs.  Obviously this skews the evaluation.  Heller writes:

Education is a curiously alchemical process. Its vicissitudes are hard to isolate.  Why do some students retain what they learned in a course for years, while others lose it through the other ear over their summer breaks?  Is the fact that Bill Gates and Mark Zuckerberg dropped out of Harvard to revolutionize the tech industry a sign that their Harvard educations worked, or that they failed?  The answer matters, because the mechanism by which conveyed knowledge blooms into an education is the standard by which MOOCs will either enrich teaching in this country or deplete it.

For me, the first step to boiling things out is to define what we mean by -- and want from -- an "education".  So, let's try to unpack why people go to college.  In most cases, Reason One is that you need a degree to get any sort of decent job.  Reason Two is to plug into a network of people -- fellow students, alumni, faculty -- that provide you a life-long community.  Of course you need a professional community for that Job thing, but also because in an otherwise anomic society you need an archipelago to seed friendships, companionships, and self-definition (or at least, as scaffolding for your personal brand: as one junior I heard on a recent college visit put it memorably, "Being here is part of the personal narrative I'm building.")  Reason Three -- firmly third -- is to get an "education" in the sense that Heller describes.  (Apropos: check this recording of David Foster Wallace's 2005 commencement address at Kenyon College.) 

Next, this hierarchy of needs then gives us a way to evaluate the prospects for MOOCs.

If organization X can produce graduates demonstrably better qualified (through objective testing, portfolios of work, and experience) to do job Y, at a lower cost, then it will thrive.  If organization X can do this better and cheaper by offering and/or curating/ aggregating MOOCs, then MOOCs will thrive.  If a MOOC can demonstrate an adequately superior result / contribution to the end outcome, and do it inexpensively enough to hold its place in the curriculum, and do it often enough that its edge becomes a self-fulfilling prophecy -- a brand, in other words -- then it will crowd out its competitors, as surely as one plant shuts out the sunlight to another.  Anyone care to bet against Georgia Tech's new $7K Master's in Computer Science?

If a MOOC-mediated social experience can connect you to a Club You Want To Be A Member Of, you will pay for that.  And if a Club That Would Have You As A Member can attract you to its clubhouse with MOOCs, then MOOCs will line the shelves of its bar.  The winning MOOC cocktails will be the ones that best produce the desired social outcomes, with the greatest number of satisfying connections.

Finally, learning is as much about the frame of mind of the student as it is about the quality of the teacher.  If through the MOOC the student is able to choose a better time to engage, and can manage better the pace of the delivery of the subject matter, then the MOOC wins.

Beyond general prospects, as you consider these principles, it becomes clear that it's less about whether MOOCs win, but which ones, for what and for whom, and how.  

The more objective and standardized -- and thus measurable and comparable -- the learning outcome and the standard of achievement, the greater the potential for a MOOC to dominate. My program either works, or it doesn't.  

If a MOOC facilitates the kinds of content exchanges that seed and stimulate offline social gatherings -- pitches to VCs, or mock interviewing, or poetry, or dance routines, or photography, or music, or historical tours, or bird-watching trips, or snowblower-maintenance workshops -- then it has a better chance of fulfilling the longings of its students for connection and belonging.  

And, the more well-developed the surrounding Internet ecosystem (Wikipedia, discussion groups, Quora forums, and beyond) is around a topic, the less I need a Harvard professor, or even a Harvard grad student, to help me, however nuanced and alchemical the experience I miss might otherwise have been.  The prospect of schlepping to class or office hours on a cold, rainy November night has a way of diluting the urge to be there live in case something serendipitous happens.

Understanding how MOOCs win then also becomes a clue to understanding potential revenue models.  

If you can get accredited to offer a degree based in part or whole on MOOCs, you can charge for that degree, and gets students or the government to pay for it (Exhibit A: University of Phoenix).  That's hard, but as a variant of this, you can get hired by an organization, or a syndicate of organizations you organize, to produce tailored degree programs -- think corporate training programs on steroids -- that use MOOCs to filter and train students.  (Think "You, Student, pay for the 101-level stuff; if you pass you get a certificate and an invitation to attend the 201-level stuff that we fund; if you pass that we give you a job.")  

Funding can come directly, or be subsidized by sponsors and advertisers, or both.  

You can try to charge for content: if you produce a MOOC that someone else wants to include in a degree-based program, you can try to license it, in part or in whole.  

You can make money via the service angle, the way self-publishing firms support authors, with a variety of best-practice based production services.  Delivery might be offered via a freemium model -- the content might be free, but access to premium groups, with teaching assistant support, might come at a price.  You can also promote MOOCs -- build awareness, drive distribution, even simply brand  -- for a cut of the action, the way publishers and event promoters do.  

Perhaps in the not-too-distant future we'll get the Academic Upfront, in which Universities front a semester's worth of classes in a MOOC, then pitch the class to sponsors, the way TV networks do today. Or, maybe the retail industry also offers a window into how MOOCs will be monetized.  Today's retail environment is dominated by global brands (think professors as fashion designers) and big-box (plus Amazon) firms that dominate supply chains and distrubution networks.  Together, Brands and Retailers effectively act as filters: we make assumptions that the products on their shelves are safe, effective, reasonably priced, acceptably stylish, well-supported.  In exchange, we'll pay their markup.  This logic sounds a cautionary note for many schools: boutiques can survive as part of or at the edges of the mega-retailers' ecosystems, but small-to-mid-size firms reselling commodities get crushed.

Of course, these are all generic, unoriginal (see Ecclesiastes 1:9) speculations.  Successful revenue models will blend careful attention to segmenting target markets and working back from their needs, resources, and processes (certain models might be friendlier to budgets and purchasing mechanisms than others) with thoughtful in-the-wild testing of the ideas.  Monolithic executions with Neolithic measurement plans ("Gee, the focus group loved it, I can't understand why no one's signing up for the paid version!") are unlikely to get very far.  Instead, be sure to design with testability in mind (make content modular enough to package or offer a la carte, for example).  Maybe even use Kickstarter as a lab for different models!

PS Heller's brilliant sendup of automated essay grading

Postscript:

The MOOC professor perspective, via the Chronicle, March 2013


May 16, 2013

Need #Data

Word cloud based on notes from a workshop not too long ago:

Need data 3

May 10, 2013

Book Review: Converge by @rwlord and @rvelez #convergebook

I just finished reading Converge, the new book on integrating technology, creativity, and media by Razorfish CEO Bob Lord and his colleague Ray Velez, the firm’s CTO.  (Full disclosure: I’ve known Bob as a colleague, former boss, and friend for more than twenty years and I’m a proud Razorfish alum from a decade ago.)

Reflecting on the book I’m reminded of the novelist William Gibson’s famous comment in a 2003 Economist interview that “The future’s already here, it’s just not evenly distributed.”  In this case, the near-perfect perch that two already-smart guys have on the Digital Revolution and its impact on global brands has provided them a view of a new reality most of the rest of us perceive only dimly.

So what is this emerging reality?  Somewhere along the line in my business education I heard the phrase, “A brand is a promise.”  Bob and Ray now say, “The brand is a service.”  In virtually all businesses that touch end consumers, and extending well into relevant supply chains, information technology has now made it possible to turn what used to be communication media into elements of the actual fulfillment of whatever product or service the firm provides.  

One example they point to is Tesco’s virtual store format, in which images of stocked store shelves are projected on the wall of, say, a train station, and commuters can snap the QR codes on the yogurt or quarts of milk displayed and have their order delivered to their homes by the time they arrive there: Tesco’s turned the billboard into your cupboard.  Another example they cite is Audi City, the Kinnect-powered configurator experience through which you can explore and order the Audi of your dreams.  As the authors say, “marketing is commerce, and commerce is marketing.”

But Bob and Ray don’t just describe, they also prescribe.  I’ll leave you to read the specific suggestions, which aren’t necessarily new.  What is fresh here is the compelling case they make for them; for example, their point-by-point case for leveraging the public cloud is very persuasive, even for the most security-conscious CIO.  Also useful is their summary of the Agile method, and of how they’ve applied it for their clients.

Looking more deeply, the book isn’t just another surf on the zeitgeist, but is theoretically well-grounded.  At one point early on, they say, “The villain in this book is the silo.”  On reading this (nicely turned phrase), I was reminded of the “experience curve” business strategy concept I learned at Bain & Company many years ago.  The experience curve, based on the idea that the more you make and sell of something, the better you (should) get at it, describes a fairly predictable mathematical relationship between experience and cost, and therefore between relative market share and profit margins.  One of the ways you can maximize experience is through functional specialization, which of course has the side effect of encouraging the development of organizational silos.  A hidden assumption in this strategy is that customer needs and associated attention spans stay pinned down and stable long enough to achieve experience-driven profitable ways to serve them.  But in today’s super-fragmented, hyper-connected, kaleidoscopic marketplace, this assumption breaks down, and the way to compete shifts from capturing experience through specialization, to generating experience “at-bats” through speedy iteration, innovation, and execution.  And this latter competitive mode relies more on the kind of cross-disciplinary integration that Bob and Ray describe so richly.

The book is a quick, engaging read, full of good stories drawn from their extensive experiences with blue-chip brands and interesting upstarts, and with some useful bits of historical analysis that frame their arguments well (in particular, I Iiked their exposition of the television upfront).  But maybe the best thing I can say about it is that it encouraged me to push harder and faster to stay in front of the future that’s already here.  Or, as a friend says, “We gotta get with the ‘90’s, they’re almost over!”

(See this review and buy the book on Amazon.com)


April 10, 2013

Fooling Around With Google App Engine @googlecloud

A simple experiment: the "Influence Reach Factor" Calculator. (Um, it just multiplies two numbers together.  But that's beside the point, which was to sort out what it's like to build and deploy an app to Google's App Engine, their cloud computing service.)

Answer: pretty easy.  Download the App Engine SDK.  Write your program (mine's in Python, code here, be kind, props and thanks to Bukhantsov.org for a good model to work from).  Deploy to GAE with a single click.

By contrast, let's go back to 1999.  As part of getting up to speed at ArsDigita, I wanted to install the ArsDigita Community System (ACS), an open-source application toolkit and collection of modules for online communities.  So I dredged up an old PC from my basement, installed Linux, then Postgres, then AOLServer, then configured all of them so they'd welcome ACS when I spooled it up (oh so many hours RTFM-ing to get various drivers to work).  Then once I had it at "Hello World!" on localhost, I had to get it networked to the Web so I could show it to friends elsewhere (this being back in the days before the cable company shut down home-served websites).  

At which point, cue the Dawn Of Man.

Later, I rented servers from co-los. But I still had to worry about whether they were up, whether I had configured the stack properly, whether I was virus-free or enrolled as a bot in some army of darkness, or whether demand from the adoring masses was going to blow the capacity I'd signed up for. (Real Soon Now, surely!)

Now, Real Engineers will say that all of this served to educate me about how it all works, and they'd be right.  But unfortunately it also crowded out the time I had to learn about how to program at the top of the stack, to make things that people would actually use.  Now Google's given me that time back.

Why should you care?  Well, isn't it the case that you read everywhere about how you, or at least certainly your kids, need to learn to program to be literate and effective in the Digital Age?  And yet, like Kubrick's monolith, it all seems so opaque and impenetrable.  Where do you start?  One of the great gifts I received in the last 15 years was to work with engineers who taught me to peel it back one layer at a time.  My weak effort to pay it forward is this small, unoriginal advice: start by learning to program using a high-level interpreted language like Python, and by letting Google take care of the underlying "stack" of technology needed to show your work to your friends via the Web.  Then, as your functional or performance needs demand (which for most of us will be rarely), you can push to lower-level "more powerful" (flexible but harder to learn) languages, and deeper into the stack.

April 08, 2013

From Big Data to Bigger Results: Focus on Ecosystemic Conditions for Analytics ROI

My guest post on the MITX.org blog

April 06, 2013

Dazed and Confused #opensource @perryhewitt @oreillymedia @roughtype @thebafflermag @evgenymorozov

Earlier today, my friend Perry Hewitt pointed me to a very thoughtful essay by Evgeny Morozov in the latest issue of The Baffler, titled "The Meme Hustler: Tim O'Reilly's Crazy Talk".  

A while back I worked at a free software firm (ArsDigita, where early versions of the ArsDigita Community System were licensed under GPL) and was deeply involved in developing  an "open source" license that balanced our needs, interests, and objectives with our clients' (the ArsDigita Public License, or ADPL, which was closely based on the Mozilla Public License, or MPL).  I've been to O'Reilly's conferences (<shameless> I remember a ~20-person 2001 Birds-of-a-Feather session in San Diego with Mitch Kapor and pre-Google Eric Schmidt on commercializing open source </shameless>).  Also, I'm a user of O'Reilly's books (currently have Charles Severance's Using Google App Engine in my bag).  So I figured I should read this carefully and have a point of view about the essay.  And despite having recently read Nicholas Carr's excellent and disturbing  2011 book The Shallows about how dumb the Internet has made me, I thought nonetheless that I should brave at least a superficial review of Morozov's sixteen-thousand-word piece.

To summarize: Morozov describes O'Reilly as a self-promoting manipulator who wraps and justifies his evangelizing of Internet-centered open innovation in software, and more recently government, in a Randian cloak sequined with Silicon Valley rhinestones.  My main reaction: "So, your point would be...?" More closely:

First, there's what Theodore Roosevelt had to say about critics. (Accordingly, I fully cop to the recursive hypocrisy of this post.) If, as Morozov says of O'Reilly, "For all his economistic outlook, he was not one to talk externalities..." then Morozov (as most of my fellow liberals do) ignores the utility of motivation.  I accept and embrace that with self-interest and the energy to pursue it, more (ahem, taxable) wealth is created.  So when O'Reilly says something, I don't reflexively reject it because it might be self-promoting; rather, I first try to make sure I understand how that benefits him, so I can better filter for what might benefit me. For example, Morozov writes:

In his 2007 bestseller Words That Work, the Republican operative Frank Luntz lists ten rules of effective communication: simplicity, brevity, credibility, consistency, novelty, sound, aspiration, visualization, questioning, and context. O’Reilly, while employing most of them, has a few unique rules of his own. Clever use of visualization, for example, helps him craft his message in a way that is both sharp and open-ended. Thus, O’Reilly’s meme-engineering efforts usually result in “meme maps,” where the meme to be defined—whether it’s “open source” or “Web 2.0”—is put at the center, while other blob-like terms are drawn as connected to it.
Where Morozov offers a warning, I see a manual! I just have to remember my obligation to apply it honestly and ethically.

Second, Morozov chooses not to observe that if O'Reilly and others hadn't broadened the free software movement into an "open source" one that ultimately offered more options for balancing the needs and rights of software developers with those of users (who themselves might also be developers), we might all still be in deeper thrall to proprietary vendors.  I know from first-hand experience that the world simply was not and is still not ready to accept GPL as the only option.

Nonetheless, good on Morozov for offering this critique of O'Reilly.  Essays like this help keep guys like O'Reilly honest, as far as that's necessary.  They also force us to think hard about what O'Reilly's peddling -- a responsibility that should be ours.  I used to get frustrated by folks who slapped the 2.0 label on everything, to the point of meaninglessness, until I appreciated that the meme and its overuse drove me to think and presented me with an opportunity to riff on it.  I think O'Reilly and others like him do us a great service when they try to boil down complexities into memes.  The trick for us is to make sure the memes are the start of our understanding, not the end of it.

March 26, 2013

Financial Services Program Management Consulting Opportunity

We're currently working with a leading investment management firm to help deploy and refine a new retirement guidance process and related tools.  As part of this, we're helping our client find a freelance project/ business manager with broad new venture launch experience (not just management of a software development project, but coordination of promotional and operational aspects as well) for the balance of 2013.  We would refer interested candidates to contract directly with our mid-Atlantic region client.  (The work would be largely on-site.)

About the role:

  • Responsibilities
    • Define and maintain granular and integrated plan for this initiative
      • Granular = day by day as needed/weekly calendar
      • Integrated = development, promotion, operational (channel) integration, etc.  NOT just development; will closely coordinate with existing project / release management on the development team
    • Track and report progress against this plan for a variety of audiences and uses
      • Includes learning and training other team members on necessary information interfaces for principal program metrics
    • Identify program dependencies, coordination requirements, delays, and resource needs in partnership with Development/Product/Promotion and Channel Integration Leaders
    • Develop and recommend options for resolving challenges
    • Work with finance staff to track  spending vs  budget
    • Coordinate with external experience design vendors as needed to support the program
    • Prepare / conduct / debrief regular team meetings (agendas, follow up notes)
    • Maintain online workspace and necessary documents to support program operations
  • Qualifications and Experience
    • 2-4 years prior program management experience with efforts of this scale
    • Understanding of/experience with software product development and promotion
    • Broad experience as a business manager preferred
    • Organized, disciplined, detail-oriented – demonstrated through prior similar efforts
    • Formal program management training ideal
  • Organizational Role
    • Reports to Program Leader
    • Peer to IT Tech Development and Business-side Product and Promotion Leaders
    • Partner with other groups as needed on integration, analytics and other topics

If you're interested, please fill out the short form below, or please pass this on to someone you know who might be a good fit!  Thanks.