What can data science do for small businesses?
The topic of applying data science to business seems to be well covered in depth. However, there are some topics on which I did not find what I was searching for. Perhaps, these topics are basic and trivial.
First, what’s a small business?
There might be a lot of definitions out there, but for me the defining criteria for a small business is that there is the one person who takes responsibility for its economic success. For this person, the so-called business owner or entrepreneur, the economic survival of this business is crucial. Hence, what would be the first question to ask? Presumably, something like ‘can my business survive’, ‘is it economically viable’?
Second, these questions come down to a fundamental equation of business, i.e. profit is the difference between revenue and costs.
Profit = Revenue - Costs
As simple as this equation is to start with, it gets complicated when you figure out the details. In particular, when time is considered. In fact, for this equation to become relevant in real application, time shall be considered.
Modelling a business, a business however tells you more precisely its status. Simulating a business or future business option might tell you, if it’s worth the effort.
Third, time series come into play. A lot can be learnt from the statistics of time series. There is also of computational support from Python and Pandas on time series.
Assumingly, some small business owners might shy away from ‘doing the math’ for their use case, because the anticipated outcome might be that stopping this business would be the logical solution. There might be an expectation or at least hope that things will turn out for the better in the future.
In conclusion, data science can help to describe the economic viability of a small business and thus support the owner to continue, to change or to stop his or her activity.