Step-by-step Guide for Becoming a Data-Driven Company

Has your company already started using AI?

According to research, it’s the right thing to do if you want to reduce costs and scale. The number of businesses that opt for AI and report it as a true asset grows every year. More than 60% of participants in a McKinsey survey claim they’ve seen revenue increases since they’ve adopted AI. 

The improvements are most notable after introducing marketing and sales AI, where companies benefit from being able to predict how likely a customer is to buy or analyze customer service.

AI helps you collect valuable data that you can further use to grow your business. In fact, data-driven companies do grow at a steadier and higher rate than an average business – over 30% annually.

Want to become one of them? Read this step-by-step guide to becoming a data-driven company.

What Is a Data-Driven Company?

A data-driven organization analyzes and interprets data to improve different business operations and decision-making processes. Its goal is to make better strategic decisions and gain an advantage in the market, as well as provide a better experience for its customers.
These companies typically use AI to help them make the most out of the data they collect, although simply using AI software doesn’t automatically make your business data-driven. It takes a bit more to truly adopt the data-driven culture in a company and here are 11 steps you can take to transition from your current business model to being a data-driven organization.

1. Standardize Your Data Flow

Are you working with huge amounts of data? Is that data too complex to tackle without a clear, systematic approach? You will undoubtedly benefit from having a seamless data flow throughout the whole process: from collecting it to applying the obtained results into your business decisions and operations.

To standardize your data flow means being able to collect data from several systems and transform them into the same format. People also call it data normalization. In it, you group similar values into a common value so you have a meaningful beginning point to:

  • Process
  • Distribute
  • And analyze data

All so the data may flow through your systems and come together at the right place at the right time.

2. Adopt a Data-Centric Culture

How do you create any company culture? Your staff needs to see the clear value of the new concept you want to adopt. If your employees know what your business strategy is, they’ll be able to understand how a data-driven organization fits into the picture.

One of the first steps to adopting a data-centric culture is to set specific goals and KPIs you can measure even before you start implementing the new systems. Share them with everyone in the company, even if they’re not very familiar with the tech field. They’ll still be able to grasp the data-driven company goals you’re trying to achieve and see how data analytics and AI can help them work more efficiently.

3. Test and Learn for Continuous Improvement

When working with AI and big databases, you need to make sure you’re always up-to-date and improving your strategy and processes.

Companies need to keep figuring out new ways to manage and interpret data and to do so, the test-and-learn tactics work pretty well. Learning from your experience will give you valuable insight into what’s working in your analytics pipeline, and what’s not providing the expected outcome. That way, you can make adjustments quickly and generate accurate and fast results for further use.

4. Include Everyone in the Decision-Making Process

As a business owner or top management, your job includes encouraging everyone on the staff to participate. Just like marketing and sales teams generate better outcomes when they work together on creating and executing strategies, your transition to becoming a data-driven business will happen smoothly if you have everyone in the company work together.

That said, bear in mind that data science shouldn’t be a process happening away from the rest of your company. If you give your data scientists a chance to work more closely with others, chances are you’ll see results very soon. Not all your staff needs to be code-savvy and able to do a data scientist’s job, but that doesn’t mean that your data should be available only to your data scientists.

5. Create Various Levels of Data Sensitivity

The levels of data sensitivity go as follows:

  • Highly sensitive
  • Averagely sensitive
  • Lowly sensitive

Highly sensitive data can dramatically impact your organization if it gets destroyed or stolen. For instance, this includes finance and login data, as well as intellectual property.

Medium-level sensitivity includes your data for internal use. However, if it were lost or destroyed, the consequences wouldn’t be as dire. For example, some internal emails and documents without confidential info.

Data that isn’t as sensitive is the one you intend for public use. For instance, your site and its content. This is just one way of structuring your data sensitivity. Yours will depend on your company’s needs.

6. Monitor the Transition

It’s not enough to just announce that from today, you’re a data-driven company. The transition will take time, and your employees will need help to adopt the new practices. To help them do it successfully, provide as much training and support as possible, but also make sure you monitor the whole process.

Some employees won’t ask for help out loud even if they need it. Be around to notice if there are hiccups and offer your assistance. Provide clear instructions and make them available at all times, and encourage teams to work together. If you set up clear goals and choose what metrics to measure before you even start with the implementation of the new system, the transition monitoring will go smoothly.

7. Acknowledge That Data Is Only the Means

What do you want to accomplish by basing your business decisions on data insights? A company’s leadership needs to understand that data collection isn’t the ultimate goal of being a data-driven business.

The goal is to find the most efficient way to analyze and interpret the data so you gain valuable insight from it and apply it to your business strategy. Avoid the mistake of hoarding the data and not doing anything with it.

And the goal of your business strategy is, of course, to provide excellent service or products to your customers, increase your revenue, and keep growing.

8. Be Patient With Data Collection ROI

As a business owner, you probably want to see ROI immediately. However, it may not be possible when you’re transitioning to being a data-driven organization. Data collection takes time, and so does data analysis, which means you’ll need to invest in AI and automation software to collect the data before you start seeing it pay off.

That means you should be patient and choose quality sources and detailed methodologies over getting quick data from unreliable sources just to speed up the process.

9. Lead Through Example

Every substantial change within a company starts at the top. The management needs to be the one to show initiative in two ways. First, they need to be supportive of the employees who are learning to embrace the new company concept. On the other hand, they should use their own example to set expectations and help the staff understand how everything will work.

That way, the data-driven company culture will be perceived as something useful and normal, not something out of ordinary. Employees will learn about the new culture on the job and be able to see the example and apply it immediately, which helps the processing speed up and generate better results.

10. Identify the Source of Uncertainty

When working with data, it’s not always possible to guarantee its reliability. Asking employees to give you absolutely certain answers doesn’t work, but here’s what does. When you evaluate the uncertainty of your data, you’re one step closer to identifying what’s wrong. And when you locate the issue, you can start fixing it immediately.

Moreover, a more focused approach to uncertainty will help your teams avoid the “hope for the best” kind of experiments. These trials need to be done but in a more controlled way. If your employees evaluate the type and level of uncertainty of the data they’re working with, they’ll be able to work with their co-workers from other teams to carry out :

  • More controlled
  • More efficient
  • And more accurate trials

This leads to getting more reliable data.

11. Focus on Helping Employees, not Just Consumers

As we mentioned, your staff will need appropriate training if you’re planning to transition from one business concept to being a data-driven company. Remember that relying on data won’t only help you make better business decisions and provide better service to your customers, but it can also be a way to motivate your employees and make them enthusiastic about their work.

Emphasize the benefits your team will experience if they learn how to work with data. They’ll be able to skip the tedious tasks they need to tackle every day. They’ll save time and be able to focus on the core of their work and be able to add new knowledge to their skillset.

A Challenge That Pays Off

Yes, becoming a data-driven company can be challenging sometimes, but it’s a process that ultimately pays off. Using data to improve your systems and provide better service leads to growth and gives you a chance to predict changes in the market and customer behavior. That means you can prepare yourself better for what the future holds.

If you believe you’re ready to start your transition, feel free to schedule a talk with our team. Let’s find out if we’re a good fit and chat about the ways we can help your business.

Start your digital
transformation today.