According to PwC research, highly data-driven organizations are three times more likely to witness considerable improvement in decision-making. Unfortunately, a whopping 62% of executives still rely more on experience and gut feelings than data to make business decisions.
It’s fine to trust your instincts every once in a while, but you should always trust data more because numbers don’t lie. Backing every decision by numbers and facts will help you make your business profitable.
Let’s take a closer look at what data-driven decision-making is, the importance of data for business, and how data can empower your employee training.
What is Data-Driven Decision-Making?
Data-driven decision-making is a process of gathering, analyzing, and deriving insights from hard data and making decisions based on that data. It’s a process that eliminates the need for shooting in the dark to make intuitive decisions.
Data decision-making starts with gathering data based on your measurable goals, that is, KPIs (key performance indicators). When you know what you need to track, and you collect all the necessary data, you analyze it to gain actionable insights.
Once you understand what your data is telling you, you can use it to develop effective strategies that help you continually optimize your business.
Importance of Data-Driven Decision-Making in Business
Using data to make decisions is vital for the continual growth of your organization. By providing you with actionable insights, data helps you predict future trends and open the door to a whole new world of business opportunities. It also enables you to improve operational efficiency and generate more revenue.
In an MIT Sloan School of Management study, professors Andrew McAfee and Erik Brynjolfsson found that data-driven companies report 4% higher productivity and 6% higher profits than their counterparts that don’t rely on data.
This data-driven approach to productivity is essential for management decision-making. Leveraging business management analytics helps you quickly identify and resolve any problems that may arise. It enables you to create predictive models and develop optimization techniques necessary for making strategic, data-driven managerial decisions.
5 Significant Benefits of Data in Employee Training
You can’t simply utilize a piece of training software, such as an LMS system, and expect to reap the rewards. You need to regularly look at your data to continually enhance the training, empower your trainees, and yield positive results.
Using data in employee training is crucial for several reasons.
1. Improving Engagement
The training itself should improve engagement, but the data that keeps rolling in will allow even more engagement. This is because you’ll work with more information about your learners, so you’ll better understand how to keep them engaged and interested in new material.
2. Personalizing the Learning Process
Personalizing the learner experience is essential for engagement and knowledge retention. Utilizing data from your chosen training software will help you create learning paths based on every trainee’s learning style and preferences. That way, they will absorb more information both efficiently and effectively.
3. Maximizing Employee Satisfaction and Retention
A lot of employees who don’t receive the job training they expect tend to leave their positions for another company that offers better L&D opportunities.
According to a Gallup report, 87% of millennials say that “professional or career growth and development opportunities” are significant to them in a job, while 69% of non-millennials agree.
Are your employees satisfied with the training you provide? Does it give them opportunities for growth? How often do you deliver proper training?
With data from your LMS system, you can gain insights into the satisfaction of your trainees, so that you can effectively meet their needs.
4. Identifying and Closing Knowledge Gaps
Your training software can also help you identify and close any potential knowledge gaps. When a trainee shows poor performance, you can pinpoint the exact areas that they have trouble with. You can instantly jump in to provide assistance and ensure that their weaknesses become strengths.
5. Making Room for New Training Techniques
Is your employee training effective? You can’t know this if you don’t measure its performance.
Utilize training software with robust reports and analytics to help you see what works and what doesn’t. The data you pull will help you make room for adjustments and adopt new training methods for more effective outcomes.
For instance, learning in the flow of work is becoming more and more popular. If it makes sense for your business and your employees’ needs, you can implement it into the training and enable your workers to apply new knowledge immediately. Then, you can measure their and your training program’s performance.
6 Steps to Making Sound Business Decisions in Employee Training
Now that you know how data can benefit your employee training efforts, it’s time to put that knowledge to practice. Here are the most vital steps for data decision-making in employee training.
1. Define Measurable Goals
You need to establish well-defined, measurable goals before conducting any kind of training. Only then will you be able to make that training effective. You’ll know where to focus your efforts and how to improve your chances of reaching the goals.
Do you want to help your workers hone certain skills? Do you want them to acquire new knowledge and abilities? Are you looking to increase productivity?
Whatever your goals are, make sure you can measure them. A good rule of thumb is to set SMART goals – specific, measurable, achievable, realistic, and timely.
2. Utilize the Right Tools for Gathering and Analyzing Data
An LMS system or training software is great for collecting and analyzing data. But you should arm yourself with more tools to gain full control of your data.
Knowledge management software is one of them. It lets you create a knowledge base for storing and accessing knowledge and bringing teams together for seamless communication and collaboration.
3. Keep your Data Organized and Up-to-Date
If your employee training data is all over the place, it would be challenging to gain insights from it. You need to collect it in a single centralized, easy-to-access repository that allows seamless data analysis.
That way, you will simplify both integration and updates. You will always pull data from a single source, and make faster, more accurate business decisions.
4. Focus on Data Protection
Ensuring the security of business data is a responsibility that goes with using data for employee training. Businesses often rely on sensitive data related to their employees and clients in the course of their day-to-day operations. So, it is important to keep such data secure and uncompromised.
As a part of your employee training program, you’ll be collecting information such as who is taking a training course, from where, and using which device and user account. That’s not all. At times, you may collect far more personal data about your clients or employees. Put in place an impregnable security apparatus as it is a question of business reputation and trust.
5. Use Visual Analytics for Faster Data Decision-Making
To make even faster and more accurate data-driven decisions, you should start using visual analytics. You can present trainees, managers, and other stakeholders with charts, graphs, infographics, and other visuals that tell the story of your data.
That way, your team will better visualize and understand the data. You will convey the message clearly and not only make the right data-driven decisions but also identify new training opportunities.
Visuals will also help you effectively turn business mistakes around. This is because you will fully comprehend all your results, understanding what you need to do to resolve any potential issues.
6. Eliminate Bias
Cognitive biases are quite common in decision-making, and it’s often challenging to be objective. Luckily, you can overcome biased behavior by focusing solely on the numbers before you – not on past experiences and other assumptions.
But how can you make sure no bias prevents you or anyone else in your organization from making a sound business decision? By creating a team of competent stakeholders who will always keep one another in check and provide insightful feedback.
According to a McKinsey Quarterly survey, organizations that reduce bias in their decision-making processes achieve up to 7% higher ROI.
Data-Driven Decision-Making Examples
Now that you know how to harness the power of data to make smart business decisions let’s explore some real examples of data-driven decision-making that you can learn from.
Google
According to the SmartData Collective case study, Google is one of the best fact-based decision-making examples. The company knows how to define clear goals, collect the right data, turn it into actionable insights, and make data-based decisions.
To see how its managers were performing, the Internet giant created the “Project Oxygen” with the goal of answering the question, “Do managers matter?”
Google’s Information Lab looked closely at performance reviews and employee surveys to see how well the managers were perceived. Using regression analysis, the social scientists in the team created a graph showing differences between two groups of managers in terms of employee happiness, team productivity, and employee turnover.
The team delved deeper into analysis to see what exactly makes a good manager at Google. They created the Great Manager Award, asking employees to provide behavioral examples regarding the best managers. They then interviewed the managers to round out all the data.
The team found top eight behaviors that make a manager great, as well as the top three behaviors that prevent them from reaching their full potential.
To act on those findings, Google implemented a biannual feedback survey, continued the Great Manager Award program, and revised its management training.
Walmart
Walmart is another excellent example of using data to make decisions that improve profitability. According to The New York Times, the retail giant used data analysis to predict what merchandise people would purchase the most in preparation for Hurricane Frances back in 2004.
Walmart analyzed terabytes of customer data from all its stores to gain insights into consumer behavior under similar conditions. The retail corporation found that Americans mostly buy beer and strawberry Pop-Tarts. The sales rate of the Pop-Tarts was seven times higher.
Those insights enabled Walmart to stock on the products with the highest demand and generate higher profits before the storm.
Amazon
Amazon is yet another example of a company good at leveraging data to make better business decisions. If you’ve ever shopped on the platform, you’ve probably come across product recommendations either via email or while browsing through the website.
Those recommendations come from data analysis. The e-commerce behemoth analyzed what its customers have previously purchased, what products they are viewing when visiting the website, what products they have reviewed and rated, and more.
That data helps Amazon recommend the right products to its customers, thus increasing its sales and generating more revenue.
Wrap Up
Data-driven decision-making is vital for optimizing a business and stimulating its continual growth. Whether it has to do with employee training, sales increase, or any other area of your business, leveraging data is what will help you thrive.
Therefore, to make the most of your data and take your decision-making to a whole new level, make sure you apply all the tips discussed above.