Data has become one of the most valuable resources a business can hold. The idea is now widely
accepted: look closely at what you collect, and you make better decisions. For most businesses,
getting the data is no longer the hard part—it piles up on its own in spreadsheets, point-of-sale
systems, and everyday tools. The real problem has shifted: it’s no longer finding the data, but
affording the people and software needed to make sense of it.
Take the owner of a small independent restaurant group—five locations and two dozen staff. Every
day, the business creates a lot of information: sales by item, table turnover, labor hours, food costs,
and seasonal demand. Most of it sits in spreadsheets and the back office of a POS system. The owner
suspects six months of this data holds real answers—which menu items actually make money, when
to add staff, and where waste is quietly eating into profits.
The obvious move is to hire an analyst. But someone with two years of experience costs ₹6–8 lakh a
year in salary alone, and the real cost climbs higher once you add benefits and insurance. On top of
that come the monthly fees for business intelligence software built—and priced—for large
companies. For a business running on thin margins, the math simply doesn’t work.
This is the gap that has long separated big enterprises from smaller operators. Large players could
afford dedicated analysts and premium software. Everyone else made decisions on instinct and
hoped for the best.
That divide is closing. With AI systems like Claude and ChatGPT, serious analysis is no longer
reserved for those who can afford a specialized team. A business owner can hand over their
spreadsheets and get real, useful insights—trends surfaced, unusual patterns flagged, and
questions answered in plain language—turning scattered data into a clear picture.
The benefit works in two ways. It gives back the existing employees a lot of time they once spent
wrestling with data they were never trained to read. And it solves the deeper problem of not having
an analyst at all. In effect, the owner and their team become “citizen analysts”—able to ask rea
questions of their own data and act on the answers. For medium-sized businesses especially, this
means growing through better efficiency, less waste, and smarter planning.
These same tools also generate images, GIFs, and videos that businesses can use for marketing and
social media—raising awareness, lifting sales, and cutting marketing costs, sometimes even opening
new income.
The result is a real leveling of the field. Analytical power that was once a privilege of size is becoming
a tool anyone can use.
— Rama Sai Lokesh Penugonda
