How a data driven culture can give businesses a competitive edge

Adopting a data friendly culture is a must in today's digital age.

With start-ups in the UK launching at a rate as fast as 80 per hour, it is essential that businesses find their competitive edge. This year, 88% of companies have named digital disruption as a priority in order to stay ahead of the game. Industry experts predict further technological innovation within businesses so failure to transform, understand, and deliver on new customer expectations could put major players at risk. Instead, smaller and more tech savvy firms could lead the way with their innovative, data driven cultures. 

To meet these expectations and deliver a great customer experience you need insight. This means being able to collect and understand data from the many different touchpoints your clients have with your business. Online and offline. This is a key driver in firms adopting big data strategies, and evolving into innovative, digital businesses. Some are already investigating the use of AI as a potential competitive differentiator. 

For businesses to truly achieve competitive edge though, it would be foolish to rely on a few key hires, to deliver on their digital data strategies. A data-friendly culture should be adopted across the whole business. So how does your business create the data-driven culture it needs? 

ITOA (IT Operational Analytics) can deliver on the basics and prevent future issues 

ITOA ensures systems are always responsive by detecting, investigating and automating both decisions and remedial actions, delivering the reliability customers expect. Reliability of products and services is an important factor for customer retention. This is where ITOA can be a key differentiator for your business, by providing a smarter way of making sure systems are always available for the customer.   

Currently, the focus is on doing this in real-time, however increasing demands and customer expectations mean that the focus is already moving to predictability of issues and 100% service availability. This in itself has its own challenges: data organisation and security, as well as having tools in place that can break down the data silos across the business. 

Use analytics to spot trends in client behaviour and enhance customer experience across your brand 

To help target clients specifically, data can be collected across the different touchpoints and client interactions, including different products, services and brands. Machine learning algorithms can ‘learn’ patterns and correlations from vast historical datasets and predict future outcomes and customer preference. This way you can spot trends and patterns in client behaviour. This will give you an opportunity to provide valuable information or offers in a timely manner for your clients based on the data collected and analysed.   

The same analytics can also be used to detect abnormal behaviour which could help fight against fraud and tackle any software issues that could be affecting the client’s customer experience.   

Use cases determine what you need from your data analysis 

By focusing on the use cases first, and then resourcing the tools to collect the data and run the analysis required to support those use cases, you allow yourself more possibility. If you start with the technology and then work out what you can do with it, you are immediately restricting yourself within the limitations of that technology. When drafting your use cases, consider if they are regulated or non-regulated and also if you need to handle real-time data for continual analysis as it is received. Your use cases may focus on areas such as customer service data, fraud prevention, regulatory and compliance requirements or IT Operations. Typically, these types of use cases involve many different departments and business areas, where they can all benefit from having access to the same underlying source of data. 

By using a data lake, different parts of the business can benefit from access to the same data. No more silos.   

A data lake is still a fairly new concept that refers to the storage of a large amount of unstructured and semi-structured data.  It is an important one as it provides a more agile way to store and manage your data compared to traditional databases and data warehouses.   

As businesses are producing increasing amounts of useful data, in various formats, speeds and sizes. To realise the full value of this data and subsequently stay ahead of the game, it must be stored in such a way that people can dive into the data lake and pull out what they need there and then, without having to define the data dictionary and relational structure of data in advance. A data lake is a flexible method of classifying and storing data and also means that you can create new sources of data from your query results, further aiding collaboration across teams and reducing resource efforts as a whole. 

Create a digital culture across the workplace, empower everyone to be data savvy   

By creating a data-friendly culture, you’re not only freeing up some very valuable, and limited, resources, such as data scientists and business analysts, you’re also empowering people across your business to make better informed decisions faster. 

Encourage people to be data-savvy, and equip them accordingly. Then, people will be able to ask, and answer, questions of their own data in an intuitive manner as the results to their queries prompt further exploration. 

A data savvy business environment will help businesses to overcome data silos and further enhance collaboration, positively impacting customer experience and facilitating competitive edge. 

Image Credit: Shutterstock / Sergey Nivens