If you run a small business, chances are you haven’t felt a
need to invest in Big Data, relying instead on your well-honed intuition to
help you hold your own against data-rich, bigger competitors. A lot of small
firm owners and managers feel that way, and in many cases they’re justifiably
proud of their competitive intangibles – a gut sense of the market and the
flexibility to change quickly.
Through funding provided by UK Government Agencies, I was
involved with a colleague in a 3-year project that provided Big Data market
intelligence from Tesco Clubcard – a leading UK store loyalty card with upwards
of 18 million members – to small food and drink producers in the Northern
Ireland region of the UK. The data covered such things as sales
performance year on year, consumer profiling (life stage & lifestyle),
basket analysis as well as regional analysis – such as best performing stores
for a small firm’s products.
The focus of our in-depth longitudinal study was seven small
food and drink producers. These small firms, ranging in size from 7 to 45
employees, sell such things as dairy products, baked goods, vegetables, and desserts
to food retailers, such as Tesco and Sainsbury.
This was the first project of its kind as Clubcard Big Data
is typically purchased by big food and drink businesses such as Unilever, P&G
and Coca Cola. Only small firms of £10 million or less turnover where eligible
for this data. Small businesses rarely have access to this kind of
data, with a key aspect of the project being the provision of the data
available to the small firms free of charge.
The level of expense typically
precludes small firms due to financial resource constraints. The data was made
available to small business by dunnhumby (the marketing consultancy firm who
manages Clubcard data). Our aim for the project was to build awareness in small
firms from various food and drink sectors (e.g. dairy, beef, pork) and a
‘taste’ of what the data could do for their business.
Small firms also often lack the expertise and time resources to exploit Big Data. The formalized structure within a statistical format requires them to take a more formalized and structured approach to marketing planning – that’s a challenge for small firms. To address this the lead researcher provided one-to-one analysis of the Big Data working with small firm owners and managers. The researcher was provided with an intensive training course before the project started by dunnhumby on interpreting Clubcard data. A key reason why this project worked was this data delivery mechanism. Big Data is only as good as the people who use it!
Typically owner-managers attended a generic workshop on a
broad category area - such as bakery products. They were then invited to submit
a request for information form. The lead researcher followed up and worked with
owner-managers on a one-to-one basis asking the ‘right’ questions and then
retrieving the most relevant data from the loyalty card database (e.g. how is
my category performing? what is the most popular flavor of bread? what type of
consumer buys a product similar to my product?). Working with the small firms
key information was distilled from the data through in-depth discussion to
provide new consumer and competitor insights.
We found that the small businesses tended to be dominated by
their owner-managers, who made decisions on the basis of their past experience
and any consumer information they could get their hands on. For example, one
firm, having been asked by a retailer to produce a range of ready meals, simply
looked at other products already on the market and tried to imitate them. In
other cases, the small firms followed guidelines laid down by the big retailer
buyers. The small firms knew they were at a disadvantage to big competitors
with the financial muscle to buy-in loyalty-card data.
Once they were given access to loyalty-card data, the
majority of the seven small firms studied took to it immediately. They
were quick to adopt a more formalized approach to marketing planning. They were
able to envision long-range innovations, rather than reacting to competitors’
or the retailers’ actions. One small firm owner said the data had
changed its ideas about how to grow its consumer base. Another said, “Now we
know precisely who our target consumer is.”
But the small firms didn't abandon their reliance on
experience. Instead, the Big Data complemented the owners and managers'
intuition, giving them new confidence. Also, the Big Data was found to
amplify the innovative dimension of the small firms’ inherent entrepreneurial
nature. This encouraged most of the small firms studied to share the data
outside of the owner-manager clique, encouraging employee involvement. As
employees outside the leadership clique were informed about the data they were
also encouraged to offer new ideas, with the workplace becoming more collegial.
To conclude, we found from the research that Big Data can be
a critical part of small firms attempts to create competitive advantage in their
markets. This is an emerging area of thinking and much more work is required to
ensure that policy and practice is informed in the adoption of Big Data by
small business.
Dr Geoff Simmons
2nd June 2016
