Gamified Analytics: Unlocking Disruptive Genius or Disrupting Data Quality?
James Kobielus 06000021Q7 firstname.lastname@example.org | 2013-04-05 11:11:16.0 | 0 Comments | 2,829 Visits
Games are fun, and fun can be a powerful force for creative genius, superhuman productivity, and, of course, personal satisfaction.
Gamification is in vogue in online
user-interface design these days. The term, defined here by Wikipedia,
refers to online environments that incorporate systems of engagement,
exploration, challenge, competition, and incentive to encourage user behaviors
that produce desirable outcomes.
Recently, there have been online
discussions of gamification in a business analytics context, such as this
article from an Ovum analyst.
Is it wise or foolish to indulge in discussions of
"gamification" where business analytics applications are concerned?
Be careful. You don't want to
gamify the governance of data and analytics. The responsibilities, roles, and
business processes must be cut-and-dried and not subject to stakeholder whim
and improvisation. You absolutely must not disrupt your "single version of
the truth" by treating data stewardship as a game that might lead to
failure. Failure is not an option where data quality is at stake.
For the same reason, you wouldn't
gamify most core business applications--such as finance, customer support,
quality assurance, supply chain management--that depend on official records,
structured workflows, and strict compliance. Business integrity depends on
maintenance of top-down, repeatable, auditable controls on the data,
transactions, analytics, orchestrations, and rules that drive these processes.
These controls are designed produce assured business outcomes. These are core
duties, not games. The staff incentives for guaranteed success are stark:
enforce these processes and outcomes or lose your jobs.
However, you might want to gamify interactive data
exploration, scenario modeling, and real-world experimentation within your data
science efforts. These activities are speculative, in the sense their success
is not guaranteed and the sequence of activities needed to produce success are
not well-understood in advance. Success on many data-science initiatives may be
due mostly to the dogged work of very smart individuals using power tools, in
which case personal curiosity and professional pride may be the most important
incentives. But gamified work environments--in which individual and team
collaborators compete for cash prizes (a la the Netflix Challenge or Kaggle
data-science contests)--might provide just enough incentive for smart people to
smart people to focus even more creatively on a fresh approach.
In leading-edge data-science challenges, perhaps what's
needed to unlock the disruptive "eureka" moment in a team of
data-science geniuses is a multi-user game designed to put them slightly
off-balance, short-circuit their old thought patterns, and encourage out-of-box
thinking. This is especially necessary when a project has a core group of data
scientists from a common discipline--such as marketing campaign analytics--who
all take the tried-and-true modeling paradigms as the default for new projects,
even when they are not entirely appropriate to some new challenge. For example,
an online game might pit various behavioral scientists against each other, with
financial incentives riding on their ability to write algorithms that
discriminate fine-grained customer sentiment from the tsunami of noise
emanating from social networks, clickstreams, and smartphones.
And you might, within bounds, find value in gamifying some
analytics-driven customer service, marketing. and back-office functions when
those processes require some ad-hoc, dynamic, and situational human judgment.
For example, handling a churn-prone customer relationship in a multichannel
environment might benefit from human touchpoints--call center,
brick-and-mortar, direct sales, etc.--competing with each other to win
"points" on their contribution to day-to-day metrics of customer
loyalty, upsell, satisfaction, etc.
One last thought. As I discussed in this blog , you might also consider using game theory to model and optimize various customer-engagement scenarios. Keep in mind, though, that this doesn't necessarily lead to "gamification" of engagements: your channels and customers may not experience game-theory-optimized interactions as a game that they can on some level "win" (other than the usual desirable outcomes of customer loyalty, satisfaction, sales, etc.).
Game-playing can be a powerfully creative activity, as long as you keep
it confined to a well-governed playing field.