How to Put a Data-Driven Strategy in Place?

by Josh Biggs in Tech on 2nd March 2021

This can’t be stressed enough: the digital revolution we are experiencing is primarily a data revolution. Modern data analysis technologies such as big data are opening up new opportunities for businesses. Data should be at the heart of decision making, whether you are a multinational corporation or a small business.

In fact, according to a 2017 MIT study, 80% of organizations see AI as an opportunity for business. 84% of them see the adoption of AI technologies in their business as a way to develop sustainable competitive advantages. In fact, data-driven companies are growing 8 times faster than the average. Putting data at the heart of your business is therefore strategic if not vital for your company’s survival.

So how do you do it? Here are some essential steps to take to achieve your digital transformation through data.

What is a Data-Driven Enterprise? 

Data-driven marketing is the discipline of acquiring, analyzing and applying all information about the customer and his wants, needs, motivations and behaviours.  A key characteristic of a data-driven culture is using data regularly to make big and small decisions. Data-driven companies establish processes and operations to make it easy for employees to acquire information, analyze it, and act on it.  Establishing a data-driven company is about data, but it is also about the people and culture in your company. 

Tips to Utilize Data Effectively in Your Business

#1 Identify the Data of Interest 

Take stock of all the data you have.  All data can be used: sales and transactional data, navigation data, operational data, machine logs, customer loyalty data.

Also, evaluate the logs and data you already have in your databases. This will allow you to set up learning models on your data. You will be able to set up predictive algorithms and analyze and predict valuable info about your business and clients. The important thing to remember is this: every company has a lot of data that can be exploited for data analysis.

#2 Engage with Every Department in Your Company to Create a Holistic Approach 

Once you have identified the data of interest, bring together the different departments in your company and map all the additional data they have at their disposal! Business experts and analysts are vital at this stage. They know businesses inside out and can help you design a strategy that will include all parts of your company. This is why data science consulting is highly advised at this stage. 

#3  Identify External Data that Would Allow You to Improve Your Models 

Did you know that you can give more weight to your available data by contextualizing it and correlating it with other data?

Weather data, road traffic data, demographic data … There are many open data sites that can provide you with key info to enrich your analysis. For example, the traffic around your stores may be correlated with the outside temperature. You can integrate this variable in analyses.

#4 Determine What You Want to Know 

We’ve discussed in considerable detail all the types of data you have to collect, how you have to ensure all departments in your business are on board, enlist the help of analysts, and even use outside data, but there’s something we’ve not discussed. What should you use all this data for? 

Because, as traditional wisdom goes, asking the right questions is as important as the answer, and this is doubly true for data analysis in the business world. Computational power is limited and expensive, and you can’t willy nilly decide to save terabytes upon terabytes of information if you don’t have a clear idea of what you want to do with them. 

This is why it is essential to create a specific list of all the questions you want to be answered and then look up what kind of information you want to answer these questions accurately, and finally, collect the pieces of data that would allow you to get this information. This is the only viable way you can fully adopt data analysis in your company without breaking the bank. 

Categories: Tech