Walking Away from the Analogy Crutch

See what I did there, with the title? I implied analogies can be like a crutch.  Good analogy huh?

I need to be transparent; I use analogies all the time.  I’m trying to quit.  OK, that may be an overstatement, but I’m trying to be more self-aware, and be sure that I’m using analogies as appropriate examples for further analysis, or to provoke more thought, as opposed to using them to represent a perfect approach or solution. 

As a consulting professional, you hope that your perspective is called upon, and as a consulting firm, providing the firm’s viewpoints is a fundamental exercise.  But insight that’s provided needs to rest on deep analysis and experience, not enticing but hollow analogies.

I can take solace in the fact that many argue humans are darn near hard-wired to use analogies, or to seek comparisons, as a way of understanding the situations presented to them:

“Symbols, metaphors, analogies, parables, synecdoche, figures of speech: we understand them.”

http://opinionator.blogs.nytimes.com/2010/11/14/this-is-your-brain-on-metaphors/?_r=0

“They begin inside the mind of an infant: A child’s first thought, the authors suggest, is ‘mommy’; the child identifies this concept with a specific physical entity, namely the caregiver who provides food and comfort… This impulse to categorize and compare stays with us, for ‘analogy is our perennial dancing partner.’”

http://www.theglobeandmail.com/arts/books-and-media/book-reviews/apples-to-apples-how-analogies-are-the-very-essence-of-human-thought/article11991899/

So why am I concerned about the use of analogies?  Because experience tells me, recognition of the limits of the analogy, especially as we traverse the digital age in business, is warranted.  And low and behold, I found some others who do a much better job of backing up my claim.  I’ve referenced science before in this blog, specifically in this post:  http://centricboston.blogspot.com/2013/01/working-on-big-data-in-business-hire.html

So I’ll double down on the criticality of scientific principles, in approaching our work, to state that a simple analogy is no substitute for true analysis.  Is it possible that after an analogy is drawn, time and effort may be spent just to conclude that the analogy that was set forth at the start was appropriate?  Yes, but that confirmation would still make the effort spent to analyze and arrive at that conclusion valuable.

Too often, people, at all levels of an organization, substitute analogies for solutions - We should be more like Apple in our product design; We should adopt the practices of Nordstrom for our customer experience, and on and on.  There’s not a problem with citing approaches or firms one admires, but again, deeper, more causal analysis should be a next step before diving into solution steps.  It’s interesting, I found this article thinking that, based on its title, ‘How Strategists Really Think: Tapping the Power of Analogy’, it would serve as an argument against my premise, but upon reading it, I noted that approximately 75% of the article’s content comes after a section “How Analogies Fail”.  

I’d encourage everyone to read the entirety of the article, but I’m going to cherry pick some ideas to suit my purposes:

https://hbr.org/2005/04/how-strategists-really-think-tapping-the-power-of-analogy

·         “Though analogical reasoning is a powerful and prevalent tool, it is extremely easy to reason poorly through analogies, and strategists rarely consider how to use them well.”

·         “Dangers arise when strategists draw an analogy on the basis of superficial similarity, not deep causal traits.”

·         “The danger of focusing on superficial similarity is very real, for two reasons. First, distinguishing between a target problem’s deep, structural features and its superficial characteristics is difficult, especially when the problem is new and largely unknown.”

·         “But this is only part of the picture. Not only is it difficult to distinguish deep similarities from surface resemblances in some contexts, but people typically make little effort to draw such distinctions.”

If it’s not clear, I’ll further highlight “people typically make little effort to draw such distinctions.”  So, that’s the viewpoint for your consideration.  Do you and does your team effectively employ analogies in your workplace?  Do you recognize their power and their pitfalls?

And for your bigger challenges, or if you’re seeking innovation, do you need to consider abandoning the analogy all together?  Maybe employ reasoning by first principles, as Elon Musk explains…

"I think it's important to reason from first principles rather than by analogy.  The normal way we conduct our lives is we reason by analogy, we are doing this because it's like something else that was done, or it is like what other people are doing.” 

What I learned about business, the consulting industry, and myself from day on the ice, curling

Nah, I'm just kidding.  With all the LinkedIn posts and work-focused blogs out there, it has become commonplace to see titles like “What the Fast and the Furious teaches us about persistence” or “The parallels between the NFL and office politics”. 

We did organize a Centric Boston team event at a curling facility and had a blast so I wanted a reason to share.  I could get all bloggy and say the game requires precision, balance, teamwork, strategy, execution, blah, blah, blah.  While all of that is true, it was just nice to spend a little time with colleagues and try something you don't get to do every day.  I'd recommend trying it if you ever get the opportunity.

Talent is not gender specific - Xconomy Forum: Tech Agenda 2015

A couple weeks back, I was able to attend the Xconomy Forum: Tech Agenda 2015, which focused on topics including Data Visualization, E-Commerce, Big Data, Cloud Computing, Mobile Marketing, Information Security, and Robots & Drones.  The half-day event was designed to deliver information through keynotes, panels, and chats by industry experts and thought leaders.

With this rich of an agenda, I could share thoughts on any number of ideas these discussions provoked for me, but instead I'm going to share an internal monologue I had at one of the breaks:

(Looking ahead at the printed agenda after the 3rd of 9 sessions):  Wait, all of the content speakers are women.  Did they do that on purpose?  How come they didn't make an announcement or hullabaloo about it?  Is it just a coincidence?  No, can't be.

(Later in the day):  So I noticed that all the speakers are women.  Did others notice?  Should I feel guilty about noticing?  I mean, they are all qualified, which was never a question in my mind anyway?  Do I notice when the speakers at an industry event are all men?  I think I'd notice that too.

Here's the link to the agenda btw - http://www.xconomy.com/boston/agenda-the-tech-agenda-2015/

After the fact, I was able to confirm that it was intentional to utilize only female speakers for this event.  Check out this post direct from Xconomy, after the event, which states, " We made it a point not to talk about “women in tech” at this event, but to let the program speak for itself. And speak it did. Here are seven highlights..." - http://www.xconomy.com/boston/2014/12/04/epidemics-inequality-and-narcissism-tech-agenda-2015-highlights/

So, while this was not the main takeaway from the event for me, I thought that it may be the most interesting thing to share for readers here.

Needless to say, the event was worth the time and I took something from every item on the agenda.  One, in particular that I connected with, was the keynote delivered by Fernanda Viegas, co-leader of Google's "Big Picture" Data Visualization Group.  The exploratory nature of trying to find ways to share data and stories was compelling.  Check out this wind visualization she highlighted:

http://hint.fm/wind/index.html

A question that pops into my head though, even in it's not focused on at conferences is in this era where the focus is Big Data, is isn't it just as important to cultivate better understanding of our small data?

Something for me to explore a bit further I guess.

Is it truly OK to fail? Bridging the gap between project execution and financial management

Why the right failure, failure you can learn and build from, should be supported in the pursuit of progress

A notion I keep reading about and hearing at IT industry events is that failure, in service of achieving objectives, is OK.  In certain cases, such as in the pursuit of innovation, failure is encouraged, because logic and experience tells us we can’t expect to know everything from the start and we will glean valuable insights from failure.  Terms such as “fail fast” and “iterate and adapt” in the IT world are almost cliché today.  I agree in the virtue of failure as part of the pursuit of excellence. Because we learn from our failures, it makes sense to include failure as part of the equation for execution on objectives.  But here’s the rub - while it’s clearly part of the equation related to project execution, allowing and accounting for failure has not gained a foothold as part of the equation in project finance. 

I was recently at a CFO technology roundtable in Boston where the idea of allowing for failures in IT initiative delivery was mentioned more than once.  For example, because Big Data is a relatively new competency, experimentation (trial and error) often means that firms start in the wrong place, such as targeting analysis before the data set has been defined and effectively architected.  CFOs, for their part, are expected to be efficient and never waste a dollar, if at all possible.  Our finance brothers and sisters are working without a net, so to speak. I’m sure they would find it more than a challenge to share the story with their C-suite peers that, “Our discretionary technology budget is 20% over forecast because we failed, and that’s OK.”  Colleagues around the table would be shooting daggers with their eyes and may be wondering if the messenger had lost their marbles.  Yet, it’s exactly the message that I believe needs to be delivered, assuming there are meaningful learnings and growth in execution that come from that failure.

Over the decades in IT, frameworks and best practices have been developed, countless books have been published and the IT discipline has evolved. Despite all of this, projects in today’s world continue to fail by some serious measures (http://www.informationweek.com/it-leadership/why-tech-projects-fail-5-unspoken-reasons/d/d-id/1109399?).  Why? Because projects are difficult to deliver.  Team dynamics, location and individual personalities, along with complex technology, lofty objectives and tight timelines, make project delivery challenging. 

I’d hazard a guess that most firms live somewhere between “so-so” and “adept” on the Success Spectrum (above) and I’m sure we all fall short of “perfection.” Maybe I’m the only one not in on the joke. But assuming I’m not, I feel that the right to fail is often more words than actions.  It sounds righteous in a speech or as part of an event panelist response, but the words are empty because very few who hold leadership roles have built to bridge connecting execution expectations to financial expectations.  I submit it’s time to build some measure of failure into projects’ financial expectations.

Of course, every firm’s leadership team is free to chart the course of their organization.  My goal is not to say that every firm needs to adopt the notion of allowing for failure in execution.  But when it comes to project delivery, since often times we are blind to many variables, the right failure, which you can learn and build from, should continue to be encouraged in the pursuit of progress.  This idea needs to be carried throughout the entire organization to reap the real benefits of the virtue of failure.  That includes accounting for failure in project finance.  Establishing exactly how to account for failure within a firm should be based on some aspects of how the firm operates.  But some simple ingredients may include:

·         Performing and up front, honest assessment across the people, process, and technology aspects being applied for the particular project

o    Are people over-allocated? Do they have the experience within the project domain? Do they understand the technologies involved?

o    Does the firm do well within certain processes, for example product management, but not as well with others like compliance initiatives?

o    Is the technology new: To the firm?  To the industry? Will the firm will be early adopters?

·         With that, there could be a unique failure quotient established for every project and that could be used as a measure to apply a percentage to quantify  how much spend can be reasonably applied in the pursuit of excellence that I mention above

What do you think?

Further Insight:

·         For a more comprehensive summary of the CFO Roundtable event, check out this article from Nicole Laskowski from Tech Target: http://searchcio.techtarget.com/opinion/CFOs-get-schooled-on-hope-and-hype-of-big-data-analytics

·         Also, there are several perspectives out there on the virtues of failure.  Here are a few highlights:

o    “Encourage senior leaders to support some risk and failure from employees as a way to foster more innovative ideas. Executives also should ensure that workers are clear about the rules and processes already in place to drive collaboration.”  http://www.usatoday.com/story/money/columnist/bruzzese/2014/01/05/on-the-job-encourage-innovation/4285947/

o    “Instead, innovation should follow a more scientific process. ‘It's about having a hypothesis, and testing it,’ he says. ‘If the results don't match your hypothesis, you've got data. If the results do match your hypothesis, then you have a discovery.’ A lot of the time, businesses don't stumble on the right path until they've gone down a few wrong ones. Figuring out what works means you have to shut a lot of ideas and projects down. That can demoralize people. The best way to soften the blow is to have everyone in the right state of mind.” http://www.businessinsider.com/why-fail-fast-isnt-good-advice-2013-11

Four themes we spotted at the Boston Big Data & Analytics unconference

At the end of March 2014, people across various industries gathered in Boston for the AnalyticsWeek Big Data & Analytics Unconference (http://boston.analyticsweek.com/).  The overarching purpose of the weeklong event, as shared by the organizers, was to spread information and capabilities across the Boston Big Data and Analytics community.

A few of my Centric Boston colleagues and I made it a point to attend - some of it at least.  Each day of the conference had a different theme and we soaked in the scenes on day one – Big Data, day three – Insurance & Financial Services, and day four – Marketing.  Although we attended discussion on different topics, several reoccurring themes emerged.  After comparing notes, here’s our recap of the top four themes:

1)    Realizing the promise. (While companies are recognizing the importance of Big Data, questions still remain about how best to take action and what kind of impact we can hope to see.)
Expectations for Big Data across industries remain huge.  Progress is absolutely being made, including great work from start-ups like DataRobot (http://www.datarobot.com/) and Nutonian (http://www.nutonian.com/) along with advancements from established players like Wayfair (http://www.wayfair.com/) and Oracle (http://www.oracle.com/index.html).  But we also heard that to get high impact outcomes and mass proliferation, there will need to be transformational thinking and broader delivery.  Two distinctive analogies about Big Data adoption were used by keynote speakers:

1.    From Paul Sonderegger (Oracle) http://merage.uci.edu/ResearchAndCenters/CDT/Resources/Documents/[197]Paul%20Sonderegger_bio.pdf: Where we are now, with Big Data is analogous to where the world stood just as electricity was invented.  The invention of electricity was revolutionary, but not every house on the block had it, initially, and many, many uses for it had not immediately been conceived.  So, we’ve done some things with Big Data, but reality is that while most companies have expectations that they will be using Big Data over the next few years, most also don’t have a clear vision of exactly how new capabilities will transform their business.  

2.     From Chris Lynch (Atlas Venture) http://www.atlasventure.com/team/chris-lynch:  The world-changing invention of the Internet came first, but to realize sweeping impacts and adoption, the subsequent inventions of the World Wide Web and Browser were required.

The focus on building momentum is undeniable, with enterprises spending about $8M on average on Big Data in 2014, according to Louis Columbus citing IDG - http://www.forbes.com/sites/louiscolumbus/2014/01/12/2014-the-year-big-data-adoption-goes-mainstream-in-the-enterprise/.  Development efforts will continue to mature and evolve into repeatable value-based activities.  Leaders will emerge!

2)  Thinking in terms of a data stream of consciousness. (Successful companies will utilize their own data, as well as data from third-party providers, to deliver context throughout the endless data collection journey.)
On both day one (Big Data) and day three (Insurance & Financial Services), points were made on what constituted a firm’s Big Data: Successful companies harness their own data, combine it with external data, and use it all to adapt to a world that’s going to change more and more quickly, leaving slower companies in its wake. When a question was posed on the Financial Services and Insurance panel about utilizing proprietary data vs. buying data from outside the firm, the simple answer was, Both are required.  Financial Services and Insurance companies aggregate data directly from their customer (demographic, preference-based, transaction history, navigation of firms’ digital media) but they are also big buyers of 3^rd party data and will continue to be.  Some examples include census data and weather data (especially for P&C Insurers).

All of this data, both structured and unstructured, will help deliver value to the firm and its customers assuming context and relevance can be established.  Think predictive analysis, including highlighting actions that can drive a customer to better personal outcomes.  Speaking of customer value…

3)  In service to our fellow man*. (When it comes to defining objectives for the use of Big Data, customers should come first. Consumer demand for transparency in actions and personalized experiences are only going to increase.)
To achieve critical adoption and value, Chris Lynch clearly put forth the notion of simplicity.  “We need data science that can be consumed by more than data scientists” (more on these scientists later).  He also highlighted that there are very real privacy concerns and natural resistance to change, so use of customers’ personal data has to deliver value and be transparent for those customers, from the start.  With that, there is a positive cycle that can be established - give me some data and I’ll provide you with answers to challenges you face in your daily lives (e.g. furniture purchasing decision, investment choices, insurance coverage, etc.).  This was especially clear on day four (Marketing) - value comes from analyzing customer behavior and buying patterns across all channels (omnichannel) to ensure a personalized shopping experience for every customer.  This draws on customer experience principles and can help in customer retention (treat people right!).  Of note: Measurement on mobile is a lot more complex than measuring traditional website activity.

If firms want to maximize the impacts they can achieve from Big Data and Analytics, they are best served to think beyond their firms’ needs and desires and instead think in terms of how to create value for their customers (businesses or consumers) with Big Data.

* This phrase was borrowed from an essay by Albert Einstein – An Ideal of Service to Our Fellow Man - http://www.npr.org/templates/story/story.php?storyId=4670423

4)  For many, the data scientist is still a mythical creature. (A consensus among experts seems to exist, that the ideal resource has a unique skillset & is difficult to find.)
The Data Scientist.  Who is this?  How do you find them?  What can you expect from them?  This was a central topic during this unconference, and has been a topic at other events we’ve attended.  Defined as, a resource who can combine technology ability (Hadoop, NoSQL, etc.) with statistical aptitude (think quant or actuary), sprinkle in some business expertise or acumen, and round it out with the ability to communicate effectively.  No wonder why there is a supposed shortage of these experts (The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise – per McKinsey http://www.mckinsey.com/features/big_data).  Nonetheless, the speakers worked to try and answer how you identify and test these resources prior to hiring them.  Some sound advice included paying particular attention to what people do as hobbies – do they have Big Data blogs? Do they opine on Big Data challenges via networking groups?  Also, specific light problems can be delivered, via the interview process, to test some aspects of problem solving. 

Another way to think about this dilemma comes from Jeff Kanel, Centric’s National Business Intelligence Practice Lead. Jeff says that it makes sense to analyze the skillsets needed for specific objectives and consider building a team of complimentary resources vs. trying to find all the skills in a single resource - http://centricconsulting.com/data-scientist-sightings-will-mostly-be-proven-a-hoax/. In fact, Centric is currently expanding its national analytics practice to fulfill current needs in this space.

So where does that leave us? The takeaways from this conference and from our own experiences point to the fact that getting a handle on Big Data is important – expectations are emerging both from corporate leaders and from consumers.  How companies specifically use the information Big Data provides, such as building teams, interpreting the data and applying that knowledge to enhance the customer experience, still remains to be seen.  Companies that invest the time to figure out such questions now will be leaders of tomorrow. 

Centric Boston colleagues Jeff Aalto, Errol Yudelman, and Brian Sedor collaborated on this piece.  http://centricconsulting.com/boston/