Becoming a Data-First Business

Data. It’s becoming increasingly valuable. As The Economist published back in 2017 “the world’s most valuable resource is no longer oil, but data”.

It’s estimated that by 2025, 463 exabytes of data will be created each day globally, equivalent to 212,765,957 DVDs per day! (World Economic Forum). The abundance of data has no effect on its value. The demand for it is so high, it’s even used as a type of currency. With people exchanging data for more knowledge or access to a wider range of services within applications.

Accelerated digital transformation has once again prompted key discussions around data, more specifically how and what businesses need to do to become data-first.

What is a Data-First Business?

Having a strategy for data has crept up the priority list for business in the past few years. As we continue to become more digital, data inevitably becomes more abundant and important.

A data-first (or data-driven) business is essentially one that makes strategic decisions based on data analysis and interpretation. The data-first approach means that the business is empowered to make better informed decisions to achieve the goal of better serving their customers, employees and other stakeholders.

Since data isn’t biased, effectively operating in a data-first way means your strategy is founded on something more than gut feelings, opinions or past experiences.

As a result, the strategy is:

1. More reliable and likely to succeed
2. Less risky
3. People and process focused

Of course, being data-first doesn’t mean you’ll always be successful the first time around since data is changeable. However, it certainly puts your business in a better position to predict future behaviour and form strategy from something that isn’t subjective.

How Does ‘Big Data’ Tie into a Data Strategy?

Since some of the datasets being handled to make strategic decisions are going to be what we now call ‘big data’, it’s crucial to consider how this ties in.

Big data is defined as being high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making and process automation (Gartner).

• Volume – Essentially the amount of data. This could be from IoT devices, social media, business transactions and many more sources. The cloud has made storing high quantities of data much easier for businesses.
• Velocity – The rate at which the data is received. For example, many cloud-based products can operate in real time, as a result this will require real time evaluation and action.
• Variety – Refers to the different types of format data is available in. Could be unstructured or semi structured, a more traditional dataset like numeric or less traditional unstructured datasets like text documents, emails or videos.

Data-first businesses use big data for key customer experience strategies like the fastest possible delivery time. Deliveroo for example use a dispatch engine they call ‘Frank’, it constantly calculates the best combination of riders to order. Using predictions for ride travel time and food preparation calculated using machine learning models based on historical data.

It’s even able to change its mind about rider assignments based on real-world events like travel delays (Silicon). Supermarkets are using similar mechanisms to ensure their routes for online shopping are as economic as possible, with some incorporating environmental considerations.

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How can my Business Become Data-First?

For business leaders, this is a key question. With data becoming increasingly important for their digital transformation journey we outline three core characteristics of data-first businesses.

1. Build a Data-First Culture

In the same way you must build a culture that embraces change for successful digital transformation, you must also build a culture that understands the importance of being data-first. While 80% of CEOs claim they have operationalised the notion of data as an asset, only 10% say their company treats it that way (Gartner).

Key to having a data-first culture is not only having the technology infrastructure in place to handle it, but also the people in place.

The data can only take the organisation so far. The real drivers are the people. 
- Alan Duncan and Frank Buytendijk, Gartner

This means:

• Hiring data-first people like chief data officers (CDOs), analysts and data managers
• Ensuring there are clear goal posts and performance reviews surrounding data
• Delivering training throughout the organisation for the management of data and dashboards and systems that display data

2. Make Data Accessible and Easy to Understand

Consider how your new systems use and present data. Do they present it in a way that’s easy to understand by the team that uses it? Can you use the data to automate next actions? Or can it notify you when the data drops above or below a certain threshold?

Whether you’re looking to optimise your workforce or better ways of customer experience management, the right tools will empower your team to become data-first.

NETX2 for example, our new SIP portal has been created to empower self-service amongst our customers. It has a wealth of features and functionality, to help businesses take control of calls and their call environment. Some of which relate highly to data management, including granular analytics and customisable real-time dashboards.

To be able to generate not just reports using NETX2, but real-time insight into call behaviour is a fantastic boost to our ability to be a responsive data-led organisation. It gives us a unified and meaningful view of the environment, saving time and effort.
- Lou Lwin, Group Head of Enterprise Architecture, Markerstudy

3. Reduce your Data Silos to Create a Single Version of the Truth

Easier said than done, but vital to work towards in becoming a data-first business. Data silos result in a serve lack of transparency, efficiency and sometimes even trust within businesses.

They usually happen when data is collected by a business tool that is isolated from the rest of your technology infrastructure. It’s vital, particularly in working towards a data-first culture to eliminate silos.

Aside from the cultural elements they also:

• Block you from having a 360-degree view of the department and therefore entire business
• Lead to bad customer experience management
• Don’t promote business growth
• Waste cloud storage space
• Threaten the accuracy of data

The good news is, you don’t need to rip out all your systems and start again to remove your data silos (unless you want to). Clever integration and cloud overlay technologies (like B•CONNECTED) can modernise and integrate your existing systems.

Moving forwards if you look to implement technology that is an all-in-one solution or is API-centric, you’ll find it much easier to reduce the amount of data silos that exist within your business.

Think People, Data, Process, Technology!

People, data, process and technology (in that order) is key methodology to consider if you’re looking to become data-first.

People:

• Consider the key players how you can get buy-in from the business
• Recruit where necessary to have more skill in handling data strategy
• Commence the data-first journey by altering your culture

Data:

• Think about the data you already have that’s not being utilised
• Assess how you can use the data to enhance the customer experience
• What data can you add to the data you already have?

Process:

• Identify where you need to start to become data-first
• Which are your biggest data related challenges?
• Review them with stakeholders to identify gaps and issues

Technology:

• You can now look at technology that will support the change to data-first
• Think about how the new technology will integrate with existing systems
• Consider if data can be easily accessed and presented across the business

As we continue to obtain more datasets, being a data-first business will be key to success. A good place to start could well be to simply use the data you’re already sitting on better. Using it to drive decisions, improve customer experience management and create efficiencies in how staff work. This could be achieved through automation technology, or something that pulls data through from your backend systems.

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