Data is power, the more data you have about your business the more efficient and profitable you can be. Today, with the help of a story we’ll illustrate how having hard data can provide insights that help you make better decisions to drive your business forward.
Story time!
Let’s say that you own a small cookie business. You sell cookies to friends, family, and some local coffee shops. With a hardback notebook, you can keep track of your entire business operation. That notebook can manage everything from procurement to production to sales to distribution. You don’t need anything more; it’s a very smooth operation!
Soon word of mouth starts making your cookies very popular. More and more shops start placing orders to include your cookies in their offerings. Next you partner with a chain of supermarkets, a few gas stations, and all of the sudden, your cookies are everywhere, and the people can’t get enough of them. Great, isn’t it?
Next, you outgrow your home kitchen and now you own a fully-fledged, though small, cookie factory; your hardback notebook is long gone as you now track everything with a management software complemented by some spreadsheets that you and your 30 employees feed information every day. These systems help you to keep production going, collect payments, and make sure your bills, taxes, contractors, and employees are paid on time. That’s all you can do with the software, right? If you are reading this, you probably know that the answer is a resounding no.
Let’s explore some opportunities on how to leverage the data you have already collected over the years; some data can provide powerful insights about your business that you never thought of.
Financial insights
Let’s talk profit margins. Having a lot of historical data about your business i.e. sales, investments, expenditures, and more gives you the power to answer some informative questions about your business, products, and investments.
By mining your own historical data, you can ask questions and get highly accurate answers. Answers and info that are not interpolated, not inferred, and do not use generic industry data. You get answers about your company, your investments and your products.
These are some of the questions you could answer:
What is your most profitable product today?
What about last season?
What about of all time?
What if we factor in the capital investments to bring it to market?
What if we consider marketing efforts to promote it?
What if we look at seasonal demand?
What if we explore the yearly cost of ingredients?
Most businesses, within their core metrics, have information that allows them to understand if they are profitable or not; but being able to talk to that data is a much more powerful proposition.
Now that we learned that our data can talk to us, let’s see how it can help us to improve our decision-making processes by making Data-Driven decisions.
Data-Driven decisions
Now that you have a lot more insights into your products and how they perform, let’s go one step further and leverage them. How can a marketing specialist who is doing online advertisement for your cookie business leverage connected data from different sources?
You have all the core metrics you need for business health, but the marketing specialist has no actual hard data, he can use Google ADS and Facebook ADS dashboards, but they both have limits.
So, let’s say you want to build a targeted marketing campaign to sell cookies to a certain group of people. To build such a campaign you need to know your audience, and in order to have those certainties, you need special tooling that allows you to build specific campaigns. You will also need special metrics to understand which platform you are performing better on.
Given the limitations of the ADS dashboards and the disconnection between that information and your own data, this is where proper Data Engineering (DE) can help your business significantly.
How? I’m glad you asked, by doing proper DE, you can merge and compare Google ADS data and Facebook ADS data to get a much more granular size of this data that you can now leverage to draw your own conclusion and make better decisions. Data-Driven and data-backed decisions will always be more efficient and effective.
Predict the future, but for real
Now the final piece of the puzzle. You have your core metrics, the marketing team is doing a great, but you noticed you bought too much flour this month and some of it has expired. Unfortunately, you basically threw money away; wouldn’t it be great if you could predict how much flour you need to buy every month? Let’s see… maybe there’s a solution, (spoiler alert), Data Engineering comes to the rescue again!
With Data Engineering you can predict how many cookies you will sell every month based on seasonal and marketing data you already have! Now that your data foretells the future, you can think ahead and plan accordingly. By maximizing your benefit, the possibilities are endless!
Conclusions
We centered our example around a cookie factory, but you can draw parallels with most businesses, because there are some universal core needs that unavoidably will produce data that can be mined, no matter the industry.
These are some of those metrics you can leverage:
- Core Metrics: Every business has its own set of historical metrics ready to be leveraged and correlated to others.
- Specialized Tactical Metrics: Each organization has its own set, some are similar through different companies like the cost-per-click on marketing, but some could be very business specific like logistic metrics.
- Future Metrics: Planning ahead with actual hard data is magical. You could profit big time by recognizing otherwise lost opportunities. For example, when the market is favorable, you can build reserves or make investments giving you the edge towards profit during a crisis. A simpler example is when you are in the off-season of your product. If you have accurate sales projections, you could buy raw materials that might be off-season as well therefore paying a much lower price.
Credits
Writers: Luis Vinay, Pedro Rossi
Reviewer: Peyton Craig
Illustrator: Dai Fiorenza
Disclaimer
In this article, AI was used to check grammar and syntax.