How to use data effectively and help your business thrive in 2023

There is the assumption that Covid-19 made everyone adapt and embrace change faster than ever before. However, it wasn't all down to the pandemic. We led the transformation, necessity made us . We had it in us all this time.

In 2023, we need to maintain momentum and continue to re-evaluate the barriers and assumptions that are holding businesses back. For example, there is an opportunity to re-consider how data can be maximised to benefit businesses in the current climate. Here are my top tips for harnessing data strategies in 2023:

1) Align data to corporate strategies

There is no doubt that businesses understand the importance of complementing intuition-driven decision-making with data-driven decision-making. Gartner predicts that by 2026 65% of B2B sales organisations will move to data-driven decision making, using technology that unites workflow, data and analytics . Historically, business leaders relied on the past for insights - looking at what worked, what didn’t and making decisions about the best path forward accordingly. Today, this model is changing; businesses not only have to deal swiftly with changing political and societal landscapes but also evolving customer behaviours. 

While this is nothing new, there is an increasing amount of data available to navigate it. However, just throwing data at the problem without first realising what you want to achieve will lead to the ineffective handling of daily tasks and data duplication as well as gaps in information. The ability to use data intelligently with a well-thought-out data strategy will help businesses sense and respond to changing market conditions effectively.

2) Streamline all processes 

The amount of data available is vast and what to do with it can seem overwhelming. Therefore, businesses need to think about their objectives, what processes they need to streamline and the best tools to achieve this.

The corporate strategy is always the starting point; this is used to define use cases and highlight where data will support them. Only once these requirements are in place will analytics be required. 

An example of this is Robotic Process Automation (RPA). It involves software workflows or scripts that simplify and streamline processes by automating high-volume repetitive, multi-step tasks. When used in conjunction with Machine Learning (ML) and Artificial Intelligence (AI), RPA can create applications that function like a human brain with the ability to adapt and evaluate based on the data provided. 

While these tools will manage data effectively and streamline processes, they are only as effective as the data provided. Also, they tend to only be practical in processes that have repetitive tasks at specific frequencies, which don’t have templates and fixed actions. Therefore, if there is a process that is partly repetitive there may be a need for RPA alongside human intelligence to achieve maximum results. 

There are a range of smart processes available to businesses seeking to increase capacity in already over-stretched workforces. They can achieve efficiency, cost reduction and a better customer journey, but must be deployed in alignment with the corporate strategy and with a clear objective to be successful.

3) Take data back to basics 

In setting up a data team and allowing them to drive strategy execution, it is important to have a radical approach to ever evolving data trends.

This can seem overwhelming. Therefore, it is important to start by getting the minimum amount of data into the cloud and prioritise where simple analytics and statistics can answer challenges. 

Once simple analytics and statistics have been used, invest in models and Machine Learning only where it benefits recurrent use cases. For example, Machine Learning models can predict when customers might leave to ensure retention of loyal customers, bringing benefits to both the customer and business. 

Finally, look at simple solutions like building products or a holistic customer view, rather than full- IT transformation.

By prioritising and taking ‘data strategies’ back to basics, many businesses will be able to act quickly and see immediate benefits that deliver a return on investment. 

The importance of digital leadership 

Yet, to digitally transform a business and to keep pace with an ever-changing world, “it is more than a technology problem; it is a leadership one” .

Digital leadership is important to create business processes that allow new technologies, products and services to be rolled out quickly and make sure all existing applications and IT operations are maintained. Ultimately, a great digital leader can improve customer satisfaction, increasing revenue and improving retention rates, as well as driving a data-first culture and new ideas. In 2023, where will your data strategy take you?