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With the colossal amount of data we all have access to, understanding how to build a data strategy has never been more important. The IDC predicts that the amount of data in the world will grow from 33 zettabytes in 2019 to 175ZB by 2025
According to my calculations… that’s a whopping growth rate of 61 percent each year!
So how do those poor CMOs, CDOs and business leaders work out how to maximise the rapidly expanding potential that data offers? The answer, surprise-surprise, lies in building an effective data strategy.
Whether you’re keen to develop a data strategy or improve your existing one, this practical guide will take you on the path to success by:
- Developing your understanding of data strategy and its importance
- Providing actionable tips on how to get started
- Showcasing data strategy models and real-life case studies
We’ll begin by exploring why building a data strategy is so important…
Why you REALLY need a data strategy
There’s an infinite amount of data – and data-driven platforms – you can draw on for your business. Most data can be leveraged to improve the performance of your organisation, whether through increased sales or improved operational efficiency.
However, a 2019 study by Domo revealed that 83 percent of marketing leaders are struggling to stay on top of everything amidst new technologies and techniques. Essentially, they are running “data blind”.
Consequently, few organisations are coming close to deriving the full value out of their data. And there are two main reasons: poor strategy or a complete absence of strategy.
The issue of data overwhelm has resulted in two common ‘dangerous’ approaches from business leaders:
1. The eager beaver: the business leader who invests in new technologies and fresh analytics without understanding how it fits in with the wider business strategy and how they will be used day-to-day.
2. The overwhelmed ostrich: the business leader who can’t bear the thought of trying to handle the complexity of the data challenge and thinks it better to make-do with outdated ways of working. (Because at least they know what they’re doing!).
Hopefully, you’re looking for a different approach. One in which you grasp the opportunity that data offers by creating an actionable data strategy.
A well thought-through data strategy improves your ability to:
- Use data in your businesses
- Make data-driven/evidence-based business decisions
- Understand what your customers think and feel
- Uncover the latest trends relevant to your business
- Deliver smarter products and services
- Improve internal operations
- Monetise data
- Stay compliant with data protection regulations
And that’s just the start.
If you can piece together the disparate parts of the data jigsaw, you can gain a competitive advantage regardless of the size of your business. According to the Insights2020 study, 67% of execs at over-performing firms were skilled at linking disparate data sources; 61% of over-performers have Insights involved in all key areas of planning; and 71% of over-performing firms combine analytical and creative thinking.
“It’s not a coincidence that many of the companies who are leaders in the market also have a good handle on their data, and how to best leverage it as a strategic differentiator.”
Donna also makes it clear that it’s not just the big players who are benefiting from data strategies but also small-to-medium-sized businesses who are realising the value of using data more strategically.
While data may be considered the new oil, it’s only valuable if you have a reliable engine. And – to extend the metaphor – the right tyres, aerodynamic set-up and other constituent parts that combine to make the thing go in the right direction without breaking down. The data strategy, then, ensures all the composite parts work well and work well together.
A more formal definition of data strategy, is provided by PwC:
“….The basic goal of data strategy is to create and maintain an enterprise-wide strategy that ensures the adequate protection, quality, value and utilization of corporate data assets…”
Key takeaway: Data has a key role to play in the success or otherwise of your business. Having a strategy to ensure you gain maximum value from data is essential. Set aside time to learn how to build a data strategy and start putting it into practice.
- PwC: defining data strategy and its importance
- Dataversity: data strategy trends in 2018
- Forbes: Why every company needs a data strategy for 2019
- The GMA: Data strategy planning: roll with the punches and see what your data can do for you.
How to get started with building your data strategy
“The emphasis should be on clarity, not volume,” he said. “Too often I see key decision makers in organisations trying to figure out how to make use of all the information they can gather. To make matters worse, they are persuaded by vendors who promise even more data insights which they insist are a “must-have” for their organisation.”
“The end result is an organisation entangled in its own data.”
The key question they need to ask then is this:
“What problem am I trying to solve?”
The objective of the data strategy should draw on two vital resources:
1. Your business strategy.
2. Your people
Drawing on your business strategy
Go through your business plan and consider how data can help you meet your corporate goals. On every page and through every section, identify the important role data has to play:
- What is the problem I need to solve?
- What kind of data would help?
- Where will I source it from?
- How will I store and safeguard it?
- How will I analyse it?
- Who will be responsible?
- How will it be shared across the team?
- How will it be implemented into the team’s working processes?
Relating data to your business strategy provides much needed focus and goes a long way to curing data overwhelm.
Drawing on your people
Every person in your organisation will likely have an idea of how data could help in their day-to-day roles. Perhaps there’s a specific data set that would help a content writer to better understand their audience, or a customer insight that would help a sales agent accelerate the route to sale.
Virtually every person in the organisation uses data or could be using data. If you haven’t already, it’s time to kickstart discussions with people in your team.
Key action point: Open up your business plan, talk to your people and work out how data can help grow your business and improve operational efficiency across the whole organisation. What problems are you trying to solve with your data?
- How to build a business strategy that grows your business – Cognetik
- Have one hour? Create a strategic plan on page – Forbes
- How to Build a Data Democratization and Data Governance Strategy – Heap
- Data may be the new oil, but it’s only valuable if you have a reliable engine – GMA
#Bonus tip: common mistakes to avoid
Beware of over-engineering your solution. With so much data available, it’s quite possible to see patterns and trends that don’t actually exist. We know that data tells stories, but sometimes they become tall tales. As Google’s Chief Digital Intelligence Engineer, Cassie Kozyrkov recently wrote, we are the sort of species that finds rabbits in clouds and Elvis Presley’s face in potato chips:
“Give humans a vague stimulus and we’ll find faces, butterflies, and a reason to allocate budget to our favorite project or launch an AI system.”
In other words, we are liable to read too much into data.
To help protect against this, here are three behaviours to avoid:
1. DO NOT collect data just because you can: There must be a clear plan and strategy in place for all the data you collect
2. DO NOT lose sight of the big picture: Big Data makes it easy to lose sight of what matters. Play it SMART instead (Specific, Measurable, Achievable, Relevant, Time-bound).
3. DO NOT present data without context: It confuses everyone. Instead present data in a way that everyone can understand, so that it relates to the wider business context. Ask yourself: how does the data relate to longer-term business goals and KPIs?
How to gain support for your data strategy
1. Transparency: share data across the business
David Siegel, CEO of Investopedia took what might be considered by some a radical step. He gave all employees at the organisation access to data detailing progress across the company. Reports were distributed to everyone, everyone was invited to weekly metrics meetings, and any employee could join any email list.
It’s worth considering that information was once a rare commodity – or at least much harder to come by than it is now. Exclusive access to information gave an individual power and so they clung to it and shared it sparingly.
But in today’s information and data rich world, it’s counterproductive. Hogging insight is bad for business. A sharing culture is much healthier. With insight shared, everyone’s wiser, everyone’s empowered to make suggestions or respond to what the data is telling them.
2. Readability: present data that anyone can understand
Data access is one thing. Understanding what it means is another. So ensuring that your data strategy makes data both accessible and understandable is of prime importance.
“The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades.”
There are many ways of communicating data, such as data visualisations, infographics and dashboards. But visualisation isn’t everything: it also needs to tell a story. Any visualisation should clearly convey what the data means and why it is important.
3. Trackability: track data that monitors business performance
As a business leader or chief marketer, you need to be able to track business performance over time across key metrics. These metrics may include areas like sales revenues and customer retention rates.
Identifying the most important business performance metrics is vitally important. It ensures you are focused on what matters most and not getting lost in the minutiae of metrics. It helps you track your overall business performance and where you stand in meeting key business targets.
If you’re failing to meet your business performance goals, then it’s time to investigate the reasons why.
Which leads us to:
4. Actionability: source data that pinpoints where to take action
Your team should have access to data insight that is not only intelligible but also actionable. In other words, it must highlight a specific problem (or opportunity) that needs addressing. Adviso provides the following example of actionable insight:
“The 12% drop in our conversion rate coincides with the introduction of our new payment gateways in the checkout flow.”
It’s specific and pinpoints a clear area that needs to be addressed urgently, i.e. the payment gateway.
Key action: Put the processes in place to ensure that data insights are shared across the business. To get started, identify insights you currently have access to that other people in the organisation could benefit from.
- Complete Transparency is key to success – Business Insider
- Data Storytelling: The Essential Data Science Skill Everyone Needs – Forbes
- How to turn your data into actionable insights – Adviso
- The Difference Between Reporting and Analysis and Why it Matters – The Data Hero Blog
How to build a data strategy: case studies and templates
Data strategies vary greatly depending on the size, nature and complexity of the business. However, the ambition and data literacy of decision-makers also plays a major role.
So what do data strategies look like in the real world? To help, we’re going to share some data strategy templates and case studies.
It’s reiterating noting that each template and strategy begins by aligning the data strategy with the business strategy and identifying the problem that needs solving. The strategy then moves onto ‘implementation processes’: these are the processes by which the objectives are putting into practice. They include: data governance procedures, technology & infrastructure, training & skills and change management.
Alternatively, this data strategy roadmap from Roadmunk illustrates how to build a data strategy in stages:
Global Data Strategy Ltd. provides four separate data strategy case studies, ranging from a consumer energy company to a professional development organisation. Each demonstrate how a data strategy was aligned to a business strategy, and the specific frameworks required to effectively utilise and govern data for their particular needs.
Key action: Start building a data strategy for your business that will meet your organisation’s most pressing needs.
- How To Develop A Data Strategy (template included) – Bernard Marr
- Data strategy roadmap: templates and examples – Roadmunk
- What’s your data strategy? – Harvard Business Review
- The Executive’s Guide to Assessing and Improving Your Data Strategy – Concepta
It’s time to see clearly
While there are many different elements to a data strategy, it must begin with an understanding of what key problem(s) you need to solve. With this key understanding, you are better placed to maximise the benefit data can provide for your business. It’s not about gathering as much data as possible, it’s about gathering the data which provides the most value.
This point was perhaps best summed up by Samir Sharma, CEO at Datazuum at a GMA Data Briefing in 2019:
Leaders must understand what data can do and how it can be harnessed. The result will be improved decision-making and the ability to foster a company culture where the true value of data is grasped by all.
Are there any data strategy tips I’ve missed? Feel free to add them in the comments below.
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