Build big data adaptability through rapid experimentation


 

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If you’re trying to waltz when
your customers want to quickstep, they’ll choose your competition.
This anxiety-inducing situation often points leaders in the direction of big data, which is a
smart move. However, most organizations approach big data with too much
trepidation — they’re dipping their toes in the water when
they should be plunging into the deep end.

Adaptable organizations experiment
rapidly with their offerings (products, services, and relationships) and build
strong discovery capabilities. There’s no better way to accelerate discovery
than to embrace big data in your strategy — the key is to attack this with
purpose and vigor. To dramatically increase adaptability, you must build an
organization that experiments in a big data fashion: with high volume,
velocity, and variety.

Volume:
a wealth of options

Big
data is classically hallmarked by high volume (exabytes), high velocity
(real-time data streams), and high variety (video, audio, and unstructured
content), and your approach to experimentation should be no different. To start, you should plan for a high volume
of experiments running at any particular point in time. You should focus your
experiments on finding the right product (or service)/market combinations; advanced companies are also experimenting with processes, value
chains, and strategies (i.e., the strategy of no strategy). You need a
high volume of experiments to hedge your bets; there’s no way to know what will
click, so you always need experiments in your innovation funnel.

The
best way to do this is to have multiple teams work on different ideas and
assign everyone the responsibility for coming up with new ideas. Google is the
paragon for innovation; employees are free to spend 20% of their time working
on whatever they feel is a good idea. A product manager I know at Apple was
assigned hundreds of resources to build whatever he thought would work. The
combination of culture (i.e., everyone is generating ideas) and structure
(i.e., multiple, parallel teams are working on experimentation) should be enough to
generate a wealth of experiments. Now you need to move these experiments
through the innovation funnel.

Velocity:
rapid execution

The
traditional sales funnel inspired me to come up with the idea of an innovation
funnel. You should have a slew of ideas that move through a pipeline to
eventually become offerings, similar to the way prospects work through a sales
funnel to eventually become customers. The difference between a sales
funnel and an innovation funnel is that, with an innovation funnel, you have much more control over how
fast ideas turn into products or services. In the spirit of big data, your
experimentation process must be extremely fast. If it takes you 18 months
to build a product that serves a fickle market, you have a huge problem.

To
increase the throughput of your experiments, take a formal approach to
improving your experimentation process. You should clearly define and communicate your
intentions to minimize the time it takes to bring an idea into the
marketplace, and then work with your big data analytics team on the key areas that
take time with the experimentation process. For instance, on a typical Six Sigma
Design of Experiments project, a signification amount of time will be spent on
data collection. By installing good tools to integrate your operational systems
with your CRM systems, you can dramatically reduce the time it takes to collect
data. Although doing a root-cause and improvement exercise takes time, you’ll see significant improvements in your innovation cycle time after only a
few of these efforts.

Variety:
the spice of innovation

They
say variety is the spice of life — it’s also the spice of innovation. If you
load your innovation funnel with experiments that all have the same theme and
your theme is off, you’ve just turned a bad situation into a worse situation.

You should
consider the array of products and services you could offer and the potential
markets they could serve, and then make sure you have a good mix at any point
in your innovation funnel. Also, don’t forget about relationships, which are
basically services that are free of charge. If your corporate strategy
involves any degree of customer loyalty, you must have relationships at least
on par with your product and service considerations.

To
prevent yourself from going insane, figure out your strategic driving force
before you start experimenting; your driving force is the locus of your
competitive advantage. For instance, a company with a products-offered
driving force builds exceptional products and experiments with markets that
could benefit from their products. Alternatively, a company with a market-driven
driving force understands a particular market extremely well and experiments
with products or services that would benefit their customers. So, even though
you want variety in your innovation funnel, you also need the structure of a
driving force to make sure you stay true to your mission and vision.

Summary

Adaptable
organizations that embrace big data for a competitive advantage double-down on
the idea of big data concepts both in content and format. Rapid
experimentation is at the core of adaptability, and big data analytics is the
best secret to rapid experimentation. At any point in time, your innovation funnel should be flooded with a
variety of ideas that are rapidly moving their way to become product, service,
or relationship offerings. 

It all starts with a mindset, so schedule time today to talk to your team about your objectives and intentions. The music in the marketplace requires a quickstep, so make sure you’re doing
the right dance.

 

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