Building a data driven business strategy: our step-by-step playbook

It doesn’t matter the size or industry of your business, embracing a data driven business strategy, using data insights and artificial intelligence is key to informed decision-making and streamlining business processes.

However, buying the best technology is not the key, we hear time and time again from our clients and the market in general is that businesses struggle to be truly data driven even after investing in new technology.

Being truly data driven is tough and you are not alone if you are facing this challenge or do not know where to start. In fact, according to a survey in the US of Fortune 1000 companies, only 19%* responded saying they have a data driven culture in their business.

This article will delve into our framework to be data driven:

• What does it mean to be data driven?
• What are the benefits of being data driven?
• How can your business be more data driven?
  o  Crafting Your Data-Driven Plan
  o  Ensuring Quality and Security of Your Data
  o  Building Strong Data Foundations
  o  Leveraging Tools & Technology
  o  Structuring a Successful Data Team
  o  Starting Small and Scaling Quickly
  o  Fostering a Data-Driven Culture

What does it mean to be data driven?

Data driven businesses are those that have the use of data embedded in their culture or DNA and they use it to support day to day decision making, streamline and automate processes, and improve the customer experience.

Developing a data analytics strategy is a core aspect of being data driven, enabling businesses to embed data use in their culture and day-to-day decision-making.

What are the benefits of being data driven?

• Smart Decision Making: Being data-driven means you make decisions based on hard facts, not just a hunch
• Risk Management: It's like having a radar for risks. You can spot and deal with potential issues early, like following rules and staying safe from cyberthreats
• Efficiency and Savings: Data-driven processes are like your personal efficiency experts. They make things run smoother, help you spend resources wisely, and cut down on waste, which saves you money
• Automation: data and AI can help you automate manual processes, saving time and money
• Customer Experience: Data helps you understand your customers like never before. You can personalise your approach, making them feel special and keeping them coming back for more
• Measuring Success: Having a data-driven culture is like having a report card for your business. You know exactly what's working and what's not
• Seeing the Future: Think of it as having a crystal ball. You can predict what's coming, so you're always one step ahead of the game

How can your business be more data driven?

1. Crafting Your Data-Driven Plan

Imagine you've acquired a pristine, empty plot of land, eager to build your very first house. Now, would you immediately order wood, nails, and windows, and start hammering away without a clear plan? Not likely. Without a strategic approach, the result might hardly resemble a house at all.

So, what's the smarter move? You'd start by engaging an architect who'd meticulously plan every detail, from the foundation to the choice of tiles. This is the essence of strategy—a comprehensive, big-picture plan that ensures your focus on what truly matters and guides you toward your ultimate goal.

Without this plan it is easy to get distracted and end up with bright shiny object syndrome.

Developing a data analytics strategy is the key starting point of any business wanting to be data driven, it sets out the plan and what everyone should focus on.

2. Ensuring Quality and Security of Your Data

Now if your data driven business strategy is your map or plan, then Data is your fuel and without it you won’t go far!

In the business world, it's easy to fall into the trap of believing that the latest and greatest tools and AI alone will propel you into the future. However, the potential of any tool is limited by the quality and availability of the data it has access to. It's akin to purchasing a sleek, high-performance sports car, only to end up pulling it with horses.

This just means you've got to make sure your data is good quality, always there when you need it, and nobody's using it in the wrong way.

To do this you need to:

1. Understanding how good your data is by conducting an audit of your data
2. Create a framework and plan for improving your data, this is where data governance comes in, setting out the framework for everyone to follow to improve the quality, availability, and security of your data
3. Target you data improvements to the data that is aligned to your data strategy and will support your adoption of AI

3. Building Your Data Fundamentals

As we discussed earlier, having access to good data is critical. This means you cannot neglect building your data foundations or enablers. It’s like building a house you wouldn’t start putting the walls up and roof on without building out solid foundations that will support them. Data is no different.

What do we mean by data fundamentals?

These are like the building blocks of data – the models and structures that let you dive into analytics, create reports, and support marketing without starting from scratch every time. They break down data silos, those places where info's scattered across different systems and is a pain to put together.

What are some examples of data fundamentals?

• Automated visual reporting available to support people to make decisions and don’t take forever to update
• A single customer view or an audience 360 dashboard. This is your one-stop shops for vital customer info. They make marketing and customer experience smoother and let you spot opportunities quickly, like cross-selling or upselling.

What are the benefits of building data fundamentals?

• They speed up getting the info you need to make decisions because your team spends less time juggling scattered data.
• Reduces risk of getting the wrong information by making sure everything’s measured in the same way, so you won’t get different versions of the same number.
• Builds trust in your data for decision-making, but reducing the number of errors
• They help you find opportunities that might slip by when you've got the big picture in front of you

Ensure that when developing a data analytics strategy you make sure that you build out your data foundations to support your business.

4. Leveraging tools and technology

It is easy to get caught up in the hype and latest technologies and end up picking the wrong tool for the job or get paralysed by the sheer choice and tech jargon out there, leading to the safe choice.

However, there are ways to cut through the noise to choose the best technology for your situation:

• Focus on the PEOPLE who will be using the tools and their needs, remember technology is an enabler, so ensure you:
  o  Skills and capability - will the technology meet the needs of the users and be easy for them to use? Will it require upskilling and change management?
  o  Performance – will it deliver the results when they need it?
  o  Scalability – will it grow and evolve in the future?
• Pick tools that naturally work well together
• Take into account how much data is involved and whether there is need for real-time processing or analysis
• Evaluate tools according to how data moves along Data Management lifecycle to understand the gaps or pain points currently
• Pick tools and technology that align to your data strategy and will set you up for the AI future

5. Structuring a Successful Data Team

Becoming a data-driven organisation requires more than just technology — you need the right people and the right processes in place for success.

The first step is to decide on how you structure your data team:

• Centre of Excellence – In a centralised setup, you've got all your data know-how packed into one department. They're the go-to folks for data collection, number crunching, creating reports, and helping everyone in the company make smart decisions.
• Decentralised Team – data experts scattered across different departments or business units. Each group takes care of their unique data needs, sort of like having mini data squads all over.
• Hybrid team – In some businesses, especially agile businesses, they agile they blend both operating models. You've got a central data team handling company-wide projects, while individual departments or units have their own data teams to tackle their specific needs. It's all about finding the right balance.

The second step is to assess the skillsets of your team and the wider business.

• What is the level of data understanding across the business?
• How commercial is the data team already in place?
• What is the technology roadmap and what skills do you need to support them?

Now, the third step is about setting up processes that act as a bridge between the those who know the business inside out and the data team. This is particularly crucial when you're using a center of excellence approach. Sometimes, the data team can be a bit separated from the those who are facing challenges and craving insights.

This often leads to the mentality of “build it and they will come” that is the killer of many data led initiatives. So, these processes make sure that what the data team comes up with is actually useful and supports the people who need it.

6. Starting Small and Scaling Quickly

If you are just starting your journey and developing a data analytics strategy, one common mistake is aiming too big right from the start, which can result in slow progress and frustrated stakeholders. Instead, prioritise quick and straightforward wins that produce measurable results to win buy-in swiftly.

• You can do this by prioritizing high value and low complexity projects, these can be identified using the prioritisation matrix (see below)
• Share learnings and success of the project to get buy-in and show the value that data can bring to the business

7. Fostering a Data-Driven Culture

You’ve got the plan, data, technology, and data team. You’re set right?! Wrong!

Often the most overlooked element of being data driven business, but the most critical is change management. Without changing the culture of the business your grand plans will most likely fail to deliver.

So, how do you go about managing change?

• Data Driven Culture at the Top: People at the top set the standards that others follow. To be truly data driven people at the top of the business need to lead through example and implement a culture of measurement and data usage.
• Communication: to bring everyone on the journey you must speak to them about the following:
  o  What is happening?
  o  Why is it happening?
  o  What are the benefits for them and the business?
  o  What is expected of them?
  o  What is the impact on them?
• Processes: ensuring they have the right processes and structures to support the adoption
• Training & Upskilling: ensure that you arm everyone with the right skills to be successful and adapt to the new technology, processes, and best practices. A key element is considering Data Literacy training.
• Measure Success: ensure you measure progress and communicate the benefits widely to increase the use of data within the business

In today's dynamic landscape, the pace of data and technological change is accelerating across businesses of all sizes and industries.

Urgency is the key—creating a data driven business strategy is essential for informed decision-making, improved efficiency, and embracing AI transformation. However, technology alone won't suffice.

Follow our seven-step framework to strategically position your business for success in this era of rapid change.

Ready to leverage your data for growth?

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This comprehensive PDF is packed with strategies to align your data with business objectives, steps to gain stakeholder support, and tactics for thriving in a changing business landscape.

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