It is no secret that for your business to be prosperous, you need to make data-driven decisions. In today’s world of constant change and innovation, companies need to embrace the idea of using data as a tool to help them grow and thrive. However, it can be difficult when you have to make a decision based on incomplete or conflicting information.
This blog post will discuss 3 best practices for making more informed decisions using data so that your company can have an edge over the competition. We’ll start by discussing the importance of collecting data from various sources to get a complete picture of what is happening within your industry or domain.
Make data-driven decisions
Society has imbued the concept of “intuition” – simply knowing when something is right or wrong. The concept of intuition has become so romanticized in modern life that it’s now a part of how many people talk about and understand the “geniuses” of our generation. Though intuition can be a convenient tool, it would be a blunder to base all decisions around a mere gut feeling. It’s only through data that you verify, understand, and quantify, and making decisions based on such insights allows us to reach conclusions and, consequently, effective results.
Making decisions based on data enables companies to create knowledge, explore business possibilities, recognize pain points, foretell future trends, optimize resources and team efforts, design new business strategies, and produce more revenue.
Furthermore, data-driven decisions help businesses to assure their continuity and progression over time. The only way for a company to adapt to this volatile environment is to make informed business decisions driven by data.
Create a culture of transparency
It’s sad perhaps but true: Because most organizations have a difficult time being transparent. Just being open and honest with your employees can give you a business advantage! It seems so simple, but it’s not. Transparency is one of the toughest values to approach in business, as many people are stuck on secrecy and fear. Having said that, establishing transparency in the workplace is key to creating a positive company culture and solidifying employee loyalty and engagement. When transparency is part of workplace culture, it brings along trust, communication, and greater levels of employee engagement and advocacy.
Although transparency can be tricky to achieve in the workplace, successful implementation could bring many worthwhile advantages to the company.
Measure your progress against goals and objectives
Everyone sets goals, it could be completing a project, personal aspirations like traveling the world, or even workplace targets. Unfortunately, setting a goal isn’t enough to get you over the line but being able to measure these goals. You need to examine a key metric and quantify your goals to help track your progress. This will also identify the mark at which you’ve completed your task. You need to be able to objectively measure success with a goal. Begin by ensuring your goal is quantifiable.
Get feedback from all levels of the organization to see how you’re doing
Whether it comes as a gut-punch or a standing ovation, feedback is one of the best ways to know if we’re doing something right or wrong. Feedback offered the right way, can grow and develop the people of your organization, improve the levels of trust and communication, and strengthen bonds between employees and managers. However, in most cases, feedback is often ignored or omitted entirely to avoid discomfort. Leaders need to establish healthy habits centered around communication and eliminate toxic ones.
A healthy culture stems from salubrious and honest feedback between employees at all layers of an organization. Making feedback sessions a part of the process from day one could subtle down the awkwardness of it.
3 best practices to follow
For many companies, a powerful, data-driven culture remains elusive, and data are rarely the universal basis for decision-making. Let’s look at the 3 best data-driven practices :
Use data to drive business outcomes: Big Data! Big Data! Big Data! Everyone is talking about Big Data and enterprises are starting to realize that simply building or purchasing a “big data” system does not automatically result invaluable, data-driven business outcomes. Having all this information but only very limited ability to drive business outcomes using that data can be futile. For several obvious and not-so-obvious reasons why organizations struggle with linking data analytics to business outcomes, and these problems aren’t just present in smaller companies. Quite the opposite actually — large corporations tend to have the toughest time extracting value from the massive amounts of data. If an organization can commence with a business predicament, create a proper structure, and accurately manage development, then it can be thriving.
Predict Customer Churn: Wondering what’s customer churn? Long story short – It is the number of customers who have unsubscribed or discontinued their service contract and customers turning their back to your service or product is no fun for any business. It is exorbitant to win them back once lost, not even thinking that they will not do the best word of mouth marketing if unsatisfied. The good news is that we can avoid a customer churn by predicting it! The basic layer for predicting future customer churn is data from the past. We look at data from customers that already have churned and their characteristics/behavior before the churn happened. Yes, there is the story that you should let sleeping dogs lie. But in the case of potential churn, it doesn’t really make sense. Being quiet and hoping that your customer does not leave will end up in a churn sooner or later. Instead don’t be scared, go out and engage with your customers. Talk to them.
Predict Staff attrition: Losing employees through staff attrition is expensive – it’s plain and simple. There are various reasons why an employee might leave your organization. However, who is going to leave, when, and why, can be elucidated based on analytical models developed as a result of data analysis and through predictive algorithms, companies gain better judgment and can undertake precautionary measures for employee attrition. When you start to focus on predicting staff attrition you will see that your hiring decisions get better.
Be patient with results – it takes time for changes in strategy to work their way through an organization; don’t give up too soon!
To get the best results, companies have to identify how they can enhance their data management processes. This can be cumbersome when data is generated in real-time from multiple sources and for organizations to take full advantage of big data, they need to foster a culture of experimentation. Evaluating and strategizing the right ideas takes time making data-driven business transformation a time-consuming process. However, focusing on the bigger picture which is becoming more competitive, and delivering higher-quality, reality-based decision making.
We hope that you have found these 3 best practices for data-driven decision-making useful and insightful. If you need help with any of the steps, we are more than happy to offer our assistance. Our team is committed to helping your business grow by effectively leveraging customer data!