The following is a guest post by Ainsley Lawrence, a freelance writer from the Pacific Northwest. She is interested in topics related to better living through education and technology. She is frequently lost in a good book.
Other than employees, there might be nothing more influential to a business’s success than data. Not only does it drive high levels of productivity, but it makes your systems, processes, and decision-making more effective. And your bottom line climbs because of it.
Many businesses say the issue with data is how much of it there is. Working through massive data sets and pulling something meaningful from them with tech tools is challenging. Manually it’s nearly impossible.
However, maybe the problem isn’t necessarily that there’s too much data. Maybe it is more so that we aren’t collecting, analyzing, and using it as effectively as we can. The tips in this article can help you with this. But first, let’s break down data analysis for businesses.
A Breakdown of Data Analysis for Businesses
Data analysis is, at its core, the collection, processing, and analysis of information. Businesses use data analysis to pull meaningful insights from data to inform their decision-making and drive their business forward.
More specifically, business leaders delve into historical business data to identify patterns, trends, causes, and other relevant insights. With this information, they can make profitable predictions and plans for their business’s future.
You could make the case that data analysis belongs in every business department. But these three are most notable.
Marketing
Marketing is at the top of the list of departments benefiting from data collection and analysis. It’s essential to know everything you can about your customers to ensure you connect with and promote your products and services to them efficiently.
Data analysis helps you take advantage of data-driven marketing. Customer data is at the crux of data-driven marketing. You use it to create personalized marketing messages for the individuals in your target audience.
Data analytics tools assist you in collecting, processing, and analyzing customer data across your digital channels and platforms. In addition, you can collect and analyze data about content, individual marketing campaigns, and channels to make productive adjustments to them.
Human Resources
Data can elevate every HR department in any industry. HR oversees each employee’s lifecycle, from recruiting to hiring to retention to development to exit. Some of their core tasks include:
- Compensation and benefits;
- Onboarding new employees;
- Training and development;
- Attracting and engaging quality applicants;
- Ensuring workplace safety and compliance.
Data is critical in each of these tasks and stages in the employee lifecycle. For example, let’s say HR sees that specific training programs are getting more participants than others.
In that case, they can look at the data to determine why. And once they do, they can change the existing training programs or scrap them all together so that resources are allocated more effectively.
Finance
When you talk about the departments that can benefit from data analysis, the finance department is a given. Businesses are constantly reviewing how to be more cost-effective in everything they do. Data can help fast-track this process.
The finance department can look at data in different business areas to see where money is going and the outcome of those investments. When they find something costing more than it’s returning, they can take a deeper look at it and make changes. They can also use data to predict possible profits in the future and use that to guide the business’s big financial decisions.
Tips for Analyzing and Using Data Effectively
Learning data analysis can sometimes be more draining than it is enjoyable. Some would say that’s absolutely the case because of its complexity. But improving your data literacy can positively impact your business’s evolution.
Apply these tips to better analyze and use data.
What do you want to know?
There’s nothing worse than collecting a lot of data with no direction. That’s when things start to get overwhelming. You have all this data with no real understanding of why you’re collecting it or what you want to learn from it. So, it just sits there with opportunities for bettering your business buried in it.
When it comes to data analysis, you have to ask yourself:
- What do I want to know?
- What am I trying to find out about my business with this data?
- What goals do I have for this round of data collection?
Write your direction down clearly and concisely. Knowing what you’re trying to gain from data simplifies data analysis and ensures actionable results.
Use all four types of data analysis
Each business leader will approach data analysis differently. However, these four types of data analysis usually make it into each approach at some point:
- Descriptive analytics — taking raw data and describing what’s happening;
- Diagnostic analytics — coming up with potential reasons why what’s happening in the data is happening;
- Predictive analytics — covering what might happen in the future based on the above;
- Prescriptive analytics — coming up with suggestions for what to do next.
You must educate yourself on each of these types of data analytics. Using a combination of them every time you’re ready to analyze data is the best way to gain a complete understanding of what the information is trying to tell you.
Don’t let data overtake you
There’s so much data out there that it can be hard to fathom getting through it all and actually garnering something meaningful from it. It can be so overwhelming that it leads to analysis paralysis. You overanalyze your data to the point you can’t get anything from it.
Don’t allow data to overtake you. Instead, be flexible in how you understand and use data. Lean on your team to get various perspectives and interpretations so you don’t have to take it all on alone. Most importantly, don’t let it control you. You’re in charge of the data and can change how you approach it whenever you need to.
Take Data Literacy One Step at a Time
You aren’t alone if you’re unsure how to collect, analyze, and use data. Data analysis can be incredibly complex and overwhelming if you allow it to be. But taking in the guidance above will help you improve your data literacy one step at a time.
It’s a very nice and informative post, Thank you for sharing the post about AI & data analysis.