Designing data practices to streamline your business
Data is the lifeblood of any business. At the end of the day, all of our decision-making processes are decided on the data we have collected in our lives, turning that data into information, and finally making decisions with it. This data could include numerical data, like your sales totals, or it could mean customer data and measuring how they interact with you. Either way, the problem is that without good data, you cannot turn it into good information and then make good decisions. Therefore, we wanted to talk about some of the best practices we have seen when applying best data practices to the businesses that we work with. So buckle up your seatbelt for the sexiest topic you'll ever read on four ways to improve your data collection and analysis in your business.
This one is a little self-explanatory, but it is the most important philosophy when talking about data. It is not helpful if you have wrong, incomplete, or unusable data in your business. Too often, we see that companies have the right intention with data, but over time the structure around it breaks down. People stop entering complete information, or there is a typo, or the data is too old to be relevant. Mistakes in the data are complicated to avoid, so cleaning the data every year or month stops the issues from piling on each other. Now we also understand that this is difficult since it is time consuming and boring, and there are likely more pressing issues for you to deal with. It is tough to carve out time to clean your business data properly. But doing this properly has resulted in exceptionally streamlined operations, which can make quick, meaningful decisions with the data they have. If you have garbage in your system, you will get garbage out of your system.
That last point leads to our second point. How do you structure your data to help avoid needing to clean it as often? Placing a solid structure around your data can prevent a significant portion of the cleanup required to keep your data usable. If it is your document, you likely have your system; you have your formats and how you want to track the data. That is great! But as soon as you want to collaborate on data collection, a strong framework becomes necessary. Everyone has their own system and framework for entering data into a system, which can quickly lead to issues, even with the best intentions. To avoid these issues, we advise removing any unnecessary data entry and making the information you collect required. Overly complicated or useless data collection will create incomplete data. No one has time to add a description of a client's whole backstory. Look at the fields you are asking people to enter and ask yourself, what am I using these for? Are they necessary? If those fields are not being used for anything, they are easy to remove and should be removed from your system. Then you can ask yourself about the remaining fields. Is there a specific set of options that can be placed here instead? How can I standardize the answers I receive? An open text box is the first step to data issues. If you can create a multiple-choice box or bubble select, you have now ensured there can never be any typos in the information you collect while making it easier for your teammates to enter data with just a few clicks.
If we are to turn data into information and then into business decisions, we also need to allow people access to it. Of course, sensitive data must be secured, but any other data can be utilized to increase collaboration across teams. When the marketing team knows where the sales team is in their numbers, they can help sales reach their goals by providing resources. If sales is capturing information about what is working with the clients, they can make marketing life much easier. These kinds of relationships work across all company sectors and help everyone achieve their goals.
Once you enable data transfer across your business, it matters which conduit you use to make the data useful. If the data is hard to access and analyze, nobody will use it. Setting up reporting templates, dashboards, and software to manipulate that data can generate exciting results to help grow your business and unlock new opportunities.
Now that you have accessible data across your business, we come to the part where we have to turn that data into information, which will then turn into decisions. But if you can't start the conversation, then your data will not amount to much, negating the need to collect it in the first place. Paving the way to creating a conversation around data can be very difficult. If your company is not leveraging data yet, then presenting the value behind data is tough because it is hard to quantify; this is why quantifying its use is what you have to do. If there is a way to say the company can save 'x' dollars or hours, that is the easiest way to convince anyone. When the answer is not that simple, persistence is the answer. Talk about all the small things that analyzing data helps to improve your day-to-day operations; they can amount to something significant. Sometimes, it is easy to forget how much analytics can help, even if you already use them. Talk about those improvements, and be excited about the efficiency you gain. As you become that center for knowledge in your business, your colleagues will begin to ask you, "how do you do it?" That is when the conversation has begun, and you can start to make sweeping changes.
If you have read through this article, then you likely understand the value of data and how to leverage it in your business. Nonetheless, we thought it was important to mention some of these things that can sometimes help keep your data bringing value to you and your company. Let us know if we are missing a great tip to help leverage data in business!