Generating Valuable Insights from Your Company Data
One of the most important assets of modern business is its data.
This is because the data can be used to gather insights into the company's customers and business which is helpful in optimising its business operations and making strategic decisions for the company's future.
However, data on its own doesn't have much value. The data has to be processed into business insights before they can be leveraged to produce business growth.
For example, data might be used to get a clearer picture of your typical customer and their demographic information. But this customer information doesn’t necessarily show how to drive business growth and improve your products and services.
In this article, we will explore how to generate valuable data insights that can help your business grow.
How to generate valuable data insights
Shifting your business to being data-driven is never easy. It represents a major investment of time and money.
Which is why many business owners and executives—especially of the old-school variety—baulk at investing so much effort and resources in something they don't really understand.
It seems like taking a major risk on something that is relatively new and unproved in the market. Or they might be confused by business analytics, or not know exactly what it entails and what it hopes to achieve.
In this article, we will give you a guide to making this transition. Firstly, you need to understand how business analytics work in practice.
There are a couple of steps you can follow to generate valuable business insights from your company data. If you follow these steps, you too can reap the tremendous benefits that so many companies and industries have gained from shifting to a data-driven approach.
Step 1. Identify key business objectives
Although it may seem as if business analytics is all about collecting, storing, and processing reams of data, it’s really the insights that are derived from the data that make business analytics so useful.
If you want to stay competitive as a business, you need the right type of data that will show you the way forward. You can have all the data in the world, but if you don't know what to do with the data, it won't do your company much good. You need to know how to process and then interpret that data to glean use from it.
The reality is in actual fact that too much data will actually hamper your ability to produce valuable business insights. Too much data can easily point you in the wrong direction. A flood of data muddies the waters and prevents you from getting a clear understanding of what strategic decisions to make in your business.
Which means that you need the correct data, not just great volumes of data. So how do you decide on which data to gather and interpret and which ones to ignore?
First, you need to assess your business and get a clear picture of your objectives. You have to decide which areas of your business are in serious need of improvement. What are the goals your business is striving towards? Try to figure out the questions you need the business analytics to answer before you even start collecting data.
When your business objectives are clearly defined, you will be able to direct your data gathering and processing efforts to only focus on those business areas that matter most to your future success and growth.
When this data is then put through processing and analysis, they are sure to give you insights in your company that will both be actionable and relevant to your current and future needs.
Step 2. Collect relevant data
After you've clearly decided on your business objectives, you can begin the task of collecting data that are relevant to these objectives.
What are the types of data you might choose to collect? One of the most obvious sources of data is customer information. Who is your customer? What is their experience with your company? Knowing your customer is crucial to your success—they are, after all, the people putting money in your coffers.
Then you might want to look closer at sales data and trends, analyse your financial data, as well as look at website traffic and page visit statistics. There might be other data points that you might consider—ones that are useful to your particular industry or may relate to your specific objectives.
When you collect data, you have to ensure that it's always as accurate as possible. You want reliable, high-quality data—not data that’s going to pull you of course.
This means that your data collecting methods have to be precise and coordinated. You might also consider using dedicated surveys, source data from external and internal databases of information, as well as using online tracking tools in your data gathering efforts.
Before you open the floodgates of data pouring into your business, you need to set limits and constraints to the data. This involves making an educated guess as to what the data will measure and what they will eventually show.
You have to predict what the data will prove. If you can do this proficiently, you will already eliminate most of the irrelevant data sets that have nothing to do with your particular business objectives.
This will allow you to decide beforehand what parameters or data sets will lead to useful information. Formulate hypotheses on different analysis outcomes before you start your data gathering. That will already point you in the right direction in terms of what data points to gather, and which to ignore.
Formulate a theory of what the data will show beforehand. This will ensure that you limit your data gathering to data which aligns with your hypothesis and business objectives.
By limiting your data sets in this way, you open the way of quickly finding out whether your initial assumptions were right or wrong. Does the data prove your original hypothesis—or do you need to change your strategy for the next round?
This is an iterative process and there’s no easy recipe for success. At every step, consider whether a particular data set points the way to adding value to your company. When you focus your data gathering activities in this way, you will be able to give all your attention to data that are actually going to help you reach your business goals.
Step 3. Analyse the data
After collecting your data, it has to be analysed. There are several ways of processing raw data. For example, you could use statistical analysis. There are also various machine learning algorithms available on the market that can do the processing for you. Another tool is data visualisation tools, which can instantly make obvious trends and behaviours in the data apparent.
To get valuable business insights, you have to use the right analysis tool for the right type of data. For example, clustering techniques are valuable for grouping customer data into segments of customers with similar behaviours and demographics.
But you won't use clustering for financial data. Here you need to identify financial trends over periods of time—which means using regression analysis.
Once you've done this initial bit of processing, you have to put the resultant data into the right context to form a logical inference from the data.
Putting data in the right context takes experience. You will probably need professional help from industry experts to point you in the right direction. Interpreting data is as much an artform as it is a science.
Don't limit your data analysis to data scientists. You will also need the help of financial experts, people proficient in sales optimization, as well as marketing specialists. Customer service reps will be able to put customer data into the right context.
What you want is to consult anyone with on-the-ground experience and real-world knowledge about the business process or market segment that you want to evaluate.
After the initial steps to analyse the data, comes the important step of interpreting the results into business insights. These should be formulated in such a way that they will shine the light on moving your company to greater profitability and growth. The business insights should be geared towards meeting those business objectives you identified right at the start of the process.
Don't overlook the way this information is presented. If no one understands the business insights you generated, no one will act on them to improve your business.
The information should be clearly presented in a way that's easy to understand and digest. Don’t try to explain massive spreadsheets to your decision makers, managers, and team members. Opt instead for presentations that are easy to read, properly designed and laid out, and clearly visualised.
This process can of course also be automated. There are several reporting tools on the market that can do an excellent job.
Pull the most important data points from your results and put them in graphs and charts that are both easy to understand and to communicate. Automated tools will be able to perform these duties in a flash, using pre prepared templates and formulas.
Step 4. Formulate an action plan
Next comes a crucial step that's often neglected—you have to take action on what you've learned.
In practice, less than half the businesses that strive to be data driven, actually manage to translate the data into a well thought-out plan of action.
Data insights don't have much value if they're not used to improve and optimise your operations. It’s well worth the effort. What’s the use of going through the trouble of collecting data, putting it through analysis software, getting a team together to interpret the results, and producing good business insights, if no one is going to implement the results to grow and improve the business?
All this work and effort cannot be the end of the road. Now that you have insight into what works and what doesn't in your business, you have to formulate a plan to put this information into good use.
Unfortunately, business insights often show you what's wrong, without giving clear direction in how to solve the problem. You have to take the business insights and formulate a strategy for how you’re going to get your business out of that rut.
That will take some experimentation to see what works. You will have to continually measure the results of any strategy you put into practice to see if it’s effective. Then you have to try again with an improved version of the strategy.
Going through this process will take courage, determination and willingness to make mistakes.
Along the way, be sure to clearly communicate your strategy to your managers, team members, and other stakeholders. You need everyone on board to make any new strategy work.
Communicate to them what data you’ve gathered as well as the conclusions you’ve drawn from the data. Then explain to them the action plan you’re putting into practice to improve your results as a company. In this way, everyone will work together as a team to make it work.
Conclusion
Transitioning a company to being data-driven is a major commitment. You need many pieces on the board to make it work.
Firstly, you need solid, reliable data. Then you need a team of analysts and market experts to interpret the data. You also need the right software and tools to do the number crunching and produce valuable business insights and logical predictions.
Then finally, you need good decision-makers that will take the resultant business insights and turn them into a business strategy that will meet your business objectives and ensure the future of your company.
Along the way, avoid becoming down by all the detail that's inherent in collecting masses of data. Always keep the bigger picture in focus and understand why you're collecting the data—and why you’re going through all this effort in the first place.
Taken together, adopting a data-drive approach is a complex affair. To make it a success, it’s crucial that all the cogs in the system fit and work together like a well-oiled machine.
In fact, you might be tempted to ask whether business analytics is even worth the effort. The success of a data-driven approach has proven its worth.
In recent surveys, it's been shown that almost 4 out of every 5 companies in the US are datadrive—more than two-thirds of all UK companies. Furthermore, companies that base their decisions on data insights have been shown to grow at an annual rate of more than 30%.
Which means it’s well worth the effort. Just decide that if you’re going the data-driven route, that you’re sticking with it all the way.
Don’t give up until you succeed in turning raw data into actionable insights. Because if you do, you will ensure the growth potential and prosperity of your business for years to come.