IoD Midlands Spring

design and produce its own even more
attractive bottle to win customers back.
Having failed in this task the team
stepped back from the problem to ask,
“what is the right question?” and “what
data do we need?”.
It turns out the right question was “how
do we sell more cola?”; the right data
related to customer needs and the answer
was to develop the plain old two-litre
plastic bottle which led to increased sales
and profits.
This is a classic example of framing the
right question and data analytic directors
and firms are much more likely to be
aware of this and to frame business
challenges in a way that improves their
outcomes.
Data vs. Intuition
In ‘Thinking Fast and Slow’ , Nobel Prize
winner Daniel Kahneman puts forward
many arguments against purely intuitive
decisions and makes a strong case for
using data analytics to augment, inform
and support important business decisions.
Roger Federer can hit a forehand in
tennis intuitively; he doesn’t have to think
about the stroke or process any thoughts
before or during the task, it just happens
automatically. However, Roger can
execute 1,000s of shot-related decisions
quickly and get instant, accurate feedback
as to whether he has got it right or wrong.
Now consider an advanced business
decision like a corporate merger. It is likely
that directors will make a handful of
decisions of this magnitude during their
careers and even then, the feedback
indicating success or failure will not be
known for many years.
The first example is a good fit for
intuition, the second example requires
that intuition be combined with accurate,
consistent, timely and applicable data to
triangulate and verify the thoughts and
views of the leadership team.
Data analytics does not mean that the
intuition of directors and leaders should
be ignored or is unimportant, but it does
provide an invaluable way to check it and,
if the two views do not triangulate, to ask
searching questions about which view is
right.
What role is left for directors
and leaders?
With evidence that data-savvy
companies significantly outperform the
data ‘have-nots’ and research
demonstrating that intuitive decision
making is flawed, what role is there for
directors and decision makers, and could
managers ultimately be completely
replaced by artificial intelligence algorithms?
Not only would such an approach raise
serious morale and ethical concerns but
the available evidence strongly suggests
that not only do directors and leaders have
a role to play but that their role is critically
important in deriving business value from
data analytics.
My very favourite data science
quotation is by Dr Mike Schmoker who
said: “Things get done only if the data we
gather can inform and inspire those in a
‘‘
We can have the top data
but all of that comes to nought
if leaders and managers do not
use it to influence and inform
critical business decisions
‘‘
position to make a difference”.
My interpretation of this famous data
quotation is that we can have the top data
scientists, the most accurate, timely and
consistent data, the most visually stunning
graphs and charts, and the very best
machine learning models, but all of that is
for nought if leaders and managers do not
use them to influence and inform critical
business decisions.
In data jargon there are three types of
data analytics:
• Descriptive Analytics looks backwards
in time at things that have already
happened and captures them in graphs,
charts and reports.
• Predictive Analytics uses historical
data and statistical techniques to make
predictions about what is likely to happen
The ‘VRIO’ framework
in the future.
• Prescriptive Analytics takes the
outputs and outcomes of the first two and
applies them to commercial decision
making to drive and optimise business
outcomes.
Prescriptive analytics is the most
important step because without it those
complex and clever descriptive and
predictive models will sit on the shelf and
will not have any impact on business
outcomes.
To achieve the benefits that have been
highlighted, including top quartile
financial performance and 20 per cent
earning increases, directors and leaders
must be fully engaged, know what
questions to ask the data experts and then
use the insight generated by data analytics
to inform high quality decisions and this
will be the subject of a future article.
Conclusions
We have explored what benefits can
accrue to companies that acquire a
mature data analytics capability, what the
strategic benefits are, how data complements
and augments intuitive decision making
and how directors and leaders play a
critical role in translating all that potential
into realised business benefits.
The ‘VRIO’ framework suggests that a
business capability must be valuable, rare,
costly for its competitors to imitate and
that the firm must be organised to capture
value from it, and that if these things hold
true a firm will realise sustained
competitive advantage.
If directors can influence their firms to
obtain and grow a data analytics capability
that passes these four tests then there is a
significant opportunity to achieve
sustained competitive advantage – and
then maybe data really will be the new oil.
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