Why Data is Important For Your Business
Data is something many small business owners are intimidated by or think is immaterial for their business’ fledgling growth. That is not the case. In fact, data is part and parcel of business operations, especially when it comes to marketing and sales. How can this be addressed?
The Harvard Business Review has a publication so named “HBR Guide To Data Analytics Basics For Managers” which details in a somewhat unchallenging way how business owners and managers can decode data. Using the book as a framework, I will detail six ways in which data can be understood and applied to ensure business growth and success.
1. Recognise The Problem Or Question
What is the problem?
This is critical. Companies that have the luxury of exponential growth e.g. Amazon or Uber or Safaricom or even a small company that is able to acquire a large contract, usually do not have any “problems”. The reason is that a lot of quick money usually covers systemic issues in many ways. It also bestows the patina of success which in itself negates the irksome issue of self-reflection.
For businesses that do not have that luxury and/or are mature, know that for growth, every department needs to be auditing its processes for continuous improvement. For the marketing department for example, if it is not executing effective marketing campaigns, then the cost of marketing will increase and there will not be commensurate revenue generation. In that situation therefore, the question is, “What is the return on advertising spend (ROAS)?” What does it need to be for sustainable short, medium and long term growth?
The key here is to be as objective as possible by framing the problem in alternative ways and in so doing bringing clarity to the issue at hand.
2. Review Previous Findings
Has any other business you know had this problem?
In most cases, the answer will be yes. At the very least, there will be some material you can get online. For it not be academic, the best way to tackle this point will be to look for similar businesses to get some guidance. Look for a business leader you admire and in the same field as you are and start a conversation. If you cannot find a business leader, find a peer. The aim is to get perspective from a mind that understands your problem from a different angle.
3. Model The Solution and Select The Variables
The solution to a ROAS could be to rejigging the marketing strategy, getting better creative assets or adding an email campaign to the marketing tactics. Nonetheless, the solution –– which is an effective marketing strategy –– needs to be defined and variables like identifying the correct online platform, determined.
4. Collect The Data
Depending on the problem and the size of the business, this can be quick or long. Using primary (surveys, experiments, questionnaires etc) and secondary (articles, journals, books etc) methods, collect the data based on the hypothesised variables. The larger the pool, the more accurate the data will be. In the marketing department’s case, it will involve meetings with the sales team, auditing creatives, interviewing customers and the like. Additionally, assessing advertising from successful competitors will go a long way in acquiring robust information that can be applied in the last stage.
Most importantly, it will be critical that the data is not cherry-picked and/or predetermined. The data needs to be collected in a manner that is empirical and unbiased.
5. Analyze The Data
What are the responses and the numbers telling you?
This is where ego needs to be thrown outside the window if the data does not fit preconceived ideas of business owners or management. Truth may be painful, but it will be liberating. On the other hand, the data may affirm the marketing department’s strategy and reveal that the low ROAS may be just that the product itself does not have a good market fit.
6. Get To Action
“All your ideas may be solid or even good. But you have to actually EXECUTE on them for them to matter.”
Gary Vaynerchuk
Ideas, data and thoughts are a dime a dozen. Where many companies fail is in executing findings. This may be for many reasons, the major one being apathy and complacency. When you look at the big and famous companies that have become a memory in the last 20 years (Kodak, Blackberry, Nokia) versus companies that have remained resilient (Microsoft), it all comes down to execution. Executives at Kodak for example had the data that a digital revolution was afoot. They did not act. Ditto Nokia in regards to the iPhone. Microsoft reinvented itself from a B2C company into a B2B organization (55% of its revenue is from office and cloud services). Satya Nadella at Microsoft is the king of execution and foresight.
To conclude, you can use data in 2 ways; the first is to look back. The second, and most important in this day of rapid and blistering innovation, is to look forward. With machine learning and AI, data can allow business owners to look forward and predict the future.