Big Data is a hot topic. And it can work wonders for the right kind of company.
As a small business, however, you are not the “right kind of company”.
The REAL gold is in your Small Data.
The Benefits of Small Data Analytics
Leveraging Small Data can provide huge gains in profitability and cash flow (some studies have shown that the increase can be as high as 50 – 60 percent). And it allows you to do it in a low-risk way, in a very short period of time (how does next week, next month, or next quarter grab you?)
Small Data is the transactional data captured by your interactions with customers, suppliers, team members, and your products and services. It’s the data that is residing in things like your accounting system, your CRM, your ERP, Excel spreadsheets, and similar small data troves.
A full-on undertaking to leverage your Small Data requires equal parts data science, programming, forensic auditing, and creativity.
Small Data Hacks
However, to get you started down your Small Data analytics journey, I’d like to give you two very effective “small data hacks” that you can use to begin apply the power of Small Data.
Try these in your company. I think you will be pleasantly surprised at what you discover.
Small Data Hack #1 – CVPM Analysis
CVPM Analysis is a way of dissecting the way your business looks from a granular, or transactional level. To do your CVPM Analysis you need to analyze your revenue, your gross profit, and your overhead on a “per transaction” basis.
What you are looking for are changes in these granular amounts over time. For example, over the last three fiscal years. Or if more relevant, over the last four most recent quarters. Generally, better insights are gained by looking at your CVPM Analysis over three full fiscal years.
Let’s look an example of two different businesses to clarify this concept. Some relevant data from each of the businesses is as follows:
| Business Alpha | Business Beta | |
| (A) Number of Customers | 1,000 | 370 |
| (B) Frequency Per Year | 0.5 | 6.0 |
| (C) Average Gross Profit | $ 350 | $79 |
| Gross Profit (A x B x C) | $175,000 | $175,380 |
This information tells us that we are looking at two businesses with completely different approaches and structures (two different business models).
Business Alpha maintains a large number of customers who only buy something about every two years (frequency of 0.5 per year), but it’s a bigger ticket item than Business Beta.
Business Beta has far fewer customers (about one-third as many), but they buy a smaller ticket item much more frequently (about every two months).
But look at the end result. Both businesses return pretty much identical Gross Profit results. Each business has about $175,000 to cover overhead expenses, repay debts, re-invest in growth, and provide a return to owners.
Small Data Hack #2 – Product Matrix Analysis
Product Matrix Analysis is a method of looking at specific customers, or customer segments, and comparing sales by product (or product category) for each customer. It provides a view of the breadth of revenue from each customer derived from your different products and services.
It usually most effective to start at more aggregated levels, and drill into more detail as the data and analyses indicate.
Product Matrix Analysis is most powerful when it is done with the following dimensions:
- Customer – sales
- Customer – revenue
- Customer – gross profit
- Market or business segment
- Geography
- Industry
The tables below provide an example to guide you:
| Sales Revenue By Customer | |
| Customer | Revenue |
| Acme | $ 35,000 |
| ACX | $ 23,600 |
| Bergstrom | $ 74,835 |
| Manilo SP | $ 126,959 |
| TOTAL | $ 260,394 |
The information contained in this first table is interesting. But it does not provide a lot of detail about the components of the revenue total for each customer. At best, it would likely lead you and your sales team to be content with Manilo SP’s volume of revenue and simply “try to sell more” to Acme and ACX.
The table below provides a more detailed, and useful view of the same customers, using the concepts of Product Matrix Analysis.
| Product Penetration Matrix (by revenue) | |||||
| Customer | Product A | Product B | Product C | Product D | TOTAL |
| Acme | $ 35,000 | $ nil | $ nil | $ nil | $ 35,000 |
| ACX | $ nil | $ nil | $ nil | $ 23,600 | $ 23,600 |
| Bergstrom | $ 12,500 | $ 19,325 | $ 1,350 | $ 41,660 | $ 74,835 |
| Manilo SP | $ 103,000 | $ 23, 009 | $ 950 | $ nil | $ 126,959 |
| TOTAL | $ 150,500 | $ 42,334 | $ 2,300 | $ 65,260 | $ 260,394 |
The information from this Product Matrix Analysis would likely lead to different conclusions.
For example, although Manilo SP looked like we should be satisfied with their revenue (when only sales revenue from the first table was used), we actually shouldn’t be satisfied at all. They are purchasing a relatively small amount of products C and D from us.
So Get Hacking
Now that you have read about these two hacks, get going with small data analytics right away.
Take the next hour or two, gather your team, and decide to apply CVPM Analysis and Product Matrix Analysis in your company.
You’ve got nothing but increased profit and cash flow to gain.
Data Concept Photo via Shutterstock
This article, “Take Advantage of These 2 Small Data Hacks to Grow Your Business” was first published on Small Business Trends