Managing Director at Portera Technologies, your thinking partner in technology and innovation.
getty
Imagine that you’re on a sailboat, sailing across the Mediterranean on a sunny day. You’ve got one eye on your dashboard, checking your heading, course over ground, true wind speed, apparent wind speed, boat speed, and so on. You’re also picking up physical and visual cues, like position of the horizon, the rate at which you’re passing landmarks, gusts and the choppiness of the water.
As a skipper, all of these data points are streaming into your brain, and you’re constantly verifying data by cross checking it with other data. Based on these inputs, you may decide to alter course, trim the sails, tack, jibe, or continue as planned.
Running a business is no different. Any top management person needs to have a reliable data strategy that provides a steady flow of accurate data that can be converted into real value. This data, monitored regularly, helps the leader make data-based decisions to drive the business forward.
Two Methods For Acquiring And Analyzing Data
There are two methods of building the right data strategy: top-down or bottom-up.
Top-down means evaluating what questions need to be answered, then creating a data strategy to answer those questions. Bottom-up is looking at the data collected from internal sales reports, third-party data companies, and other sources, and working backward to answer questions.
A top-down approach enables you to prove the value quickly to the business. Since you are answering business critical questions, the impact of acting on the findings is greater. In the words of Lucius Annaeus Seneca, “If one does not know to which port one is sailing, no wind is favorable.”
Components Of An Effective Data Strategy
There are four components of an effective data strategy. When all four components are properly constructed and aligned, they come together to provide accurate, reliable data that supports business objectives and offers real value.
1. Business strategy: Decide which questions you want the data to answer, and then explore which KPIs and metrics will help to reveal that answer. You may want to know what type of content will help sales, or you need to track where products are along the transportation chain, etc. When the questions that need answering have been defined, this will direct the path of your data collection.
2. Roles and governance: Within your organization, make sure you and your team are knowledgeable about the different responsibilities in regards to data. Know who is in charge of what data, what questions you can ask, and what types of reports are available.
3. Data management: The data you work from needs to be secure, clean and accurate. This happens best with a “privacy by design” approach in the collection and storage of data. Whether you’re using internal data or data from a third party, make sure it is protected from security breaches, adheres to national privacy standards, and is accurately cleansed to get rid of out-of-date or incorrect information.
4. Technology: The tech you can use to collect and store data varies widely, so make sure you’re using something that suits your needs without going overboard. Understanding what types of outcomes you want can help you find the right tech solutions for your business. If you’re not sure which platform or software to choose, talk to your data engineers. They’ll be able to help.
Troubleshooting Your Data Process
In my work helping businesses answer their biggest questions about data, I’ve seen again and again that the biggest problem companies have is disorganization. Even if you have all the components listed above and execute your strategy perfectly, it’s hard to find answers in a giant pile of disorganized data. Make sure your files are organized and documented to the nth degree.
Availability of data is another issue. Sometimes, you just can’t access the data you want. Maybe it’s locked down with privacy restrictions, just doesn’t exist, isn’t granular enough, or you can’t find the frequency you are looking for. There’s always a workaround. You may need to ask a slightly different question to get the right answer. Recreate the process with different data points.
The most painful, yet fixable, problem in the data process is a lack of competence in finding and translating the data. If you or your staff don’t feel comfortable doing data collection and analysis yourselves, hire an outside company to do it for you until you become proficient enough to do it yourself.
How To Use The Data You’ve Collected
You’ve gone through the process, worked with your data partners, ran in-house reports, and now it’s time to make sure your data supports the questions you set out to answer.
Take your data and use it to visualize answers to your original questions. Does it actually and accurately provide clear answers to your questions? If it does, then use the data to make data-driven decisions that propel your business forward.
If you’re not seeing clear answers from the data you collected, it may be time to go back through the process and see where your original data collection process went off the rails. Would there be a better origination point for data that would provide clearer answers? Is it possible that the data you collected came from out-of-date or unclean sources? Go back, figure out what went wrong, and try again.
Data Collection And Analysis Is Complex, But It’s Worth The Effort
Rather than making decisions based on guessing, trial and error, or bias, data allows you to make certain, confident decisions for your business. Relying on accurate data for decision-making can help you achieve better outcomes that help you scale intelligently.
Don’t let the complexity of the data collection and analysis process intimidate you. If you’ve ever wished for a partner that can help you make tough business decisions, data is it.
Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
