How Data Science Helps Small Businesses

Here’s a staggering fact: an estimated 90%
of startups fail. Most often this happens in their second through
fifth years, which is when the company has launched a product and is time to execute. At this stage, resources continue to be very
limited and there is little room for error. It is up to leadership to adopt a strategy
that will turn challenges into advantages. But that is easier said than done. Very often, entrepreneurs find themselves
caught in what we like to call the ‘’live to fight another day’’ trap. With multiple pressing operating issues, few
skilled employees, and a bottom line in red, startup founders and small business owners,
in general, feel that investment in data strategy, data collection, and data analysis is a luxury
that they simply cannot afford because they need to dedicate their energy on actions that
will produce results now, rather than in a year. This mindset is reminiscent of Gil Amelio,
who was Apple’s CEO before Steve Jobs took over.

In a question on how the tech company was
doing, he famously said: “Apple is like a ship with a hole in the bottom, leaking water, and my
job is to get the ship pointed in the right direction ”.
If you’re the captain of a ship that’s leaking water, would you try to point it in
the right direction or would you try to do something about the hole in its structure
instead? Similarly, if you run a business without knowing
where exactly you’re headed, would you continue to work harder but be essentially blind to
growth, or should you invest in data that will point you in the right direction? Yes, small businesses have very scarce resources
– and it is precisely why they cannot afford to waste any of them. The only way to ensure that they make the
most out of what they have is to adopt data-driven decision-making. At this point, you might be asking, “Can
all small businesses benefit from data? Isn’t this framework mostly beneficial for
digital startups rather than traditional firms?” That’s a common misconception.

In reality, if your company needs to understand
its customers and find ways to offer a better product, or if you are interested in running
a business that is more operationally efficient, then you certainly need to give data strategic
importance. Let’s see how data can help a traditional
and a digital business respectively through a real-world scenario – consider a chain
of 3 brick-and-mortar bookstores and an exclusively-online book retailer, all of which started operating
a year ago. Presumably, the brick-and-mortar stores do
not have as much data as the digital business, which puts them at a slight disadvantage. Nevertheless, management has multiple options
to utilize data and begin collecting insights.

What they can do is:
– Place sensors that detect mobile phone signals on shop windows to collect information on
footfall to ensure stores are in areas with sufficient customer traffic. – Monitor how many people enter the stores
in order to experiment with promotional messages and different arrangements of shop windows
to try and attract more engagement. – Combine the collected information with the
number of store visitors who end up purchasing one or more books. In this way, management will be able to gain
an idea of the conversion rate for each store and explore whether this benchmark is consistent
across all three locations. – Use the insights to understand if and why
one location is doing much better than the rest and then apply these good practices in
the other stores as well. – Analyze sales receipts and gather this data
in spreadsheets – or a BI tool – in order to find the relationship between store discounts
and volumes sold, thus gaining an idea about price sensitivity. – And lastly, build a dashboard that helps
track performance at the store level and shows how different genres and types of promotions
are performing throughout the year.

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