Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.
Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’
Bernard Marr ist ein weltbekannter Futurist, Influencer und Vordenker in den Bereichen Wirtschaft und Technologie mit einer Leidenschaft für den Einsatz von Technologie zum Wohle der Menschheit. Er ist Bestsellerautor von 20 Büchern, schreibt eine regelmäßige Kolumne für Forbes und berät und coacht viele der weltweit bekanntesten Organisationen. Er hat über 2 Millionen Social-Media-Follower, 1 Million Newsletter-Abonnenten und wurde von LinkedIn als einer der Top-5-Business-Influencer der Welt und von Xing als Top Mind 2021 ausgezeichnet.
Bernards neueste Bücher sind ‘Künstliche Intelligenz im Unternehmen: Innovative Anwendungen in 50 Erfolgreichen Unternehmen’
How Do You Develop A Data Strategy? Here’re 6 Simple Steps That Will Help
2 July 2021
Whether you’re a big data giant like Facebook or Google, or a small, family-run business, all smart business starts with strategy. And these days, every company, big or small, in any industry, needs a solid data strategy.
There are millions of ways data can help a business but, broadly speaking, they fall into two categories: one is using data to improve your existing business and how you make business decisions. The second is using data to transform your day-to-day business operations. In practice, most companies start out wanting to improve their decision making and take it from there. However, if you want to use data, you must always start with a data strategy. What data you gather and how you analyse it will depend entirely on what you’re looking to achieve – so you need to have thought about this at the outset. Having a data strategy helps the whole process run more smoothly and prepares you and your people for the journey ahead.
Tips for Creating a Robust Data Strategy
Getting the key company players and decision makers involved will help you create a better data strategy overall, and getting their buy-in at this crucial early stage means they’re more likely to put all that data to good use later on.
Keep in mind that, like any business improvement process, things may shift or evolve along the way. You may find that your data points to interesting new questions that you want to explore or leads to modifications to your existing data strategy. If that happens, simply revisit your data strategy, re-evaluating each of the points below in turn.
The Six Components of a Data Strategy
A good data strategy should answer the following key questions:
1. What do I need to know or what business problem do I need to solve? Rather than starting with the data itself (i.e. what you already have, what you might be able to get access to, or what you would love to have), it’s much better to start with company objectives. After all, why bother collecting data that won’t help you achieve your business goals?
Think about the strategic priorities you’ve laid out for the coming months or years. Define what it is you want to achieve and then think about the big unanswered questions you need to answer to deliver that strategy. In short, work out what it is you need to achieve through data. Are you looking to reach more customers, better understand your current ones, or determine where the best locations are to provide your service?
2. What data do I need to answer my questions? In this age of big data it is even more important to think small. I recently worked with one of the world’s largest retailers and, after my session with the leadership group, their CEO went to see his data team and told them to stop building the biggest database in the world and instead create the smallest database that helps the company to answer their most important questions. This is a great way of looking at data.
Look at each question you’ve identified and then think about the ideal data you would want or need to answer that question. Once you have defined the ideal data, look inside the organisation to see what data you already have. Then look outside and establish what data you could have access to. But remember, only by knowing what data you need will you know where to look for it, and how to collect it.
3. How will I analyse that data? Once you’re clear about your information needs and the data required, you need to define your analytics requirements, i.e. how you will turn that data into insights that help you answer your questions and achieve your business goals.
Traditional data collection and analysis is one thing – like point of sale transactions, website clicks, etc. – but where much of the promise of data lies is in unstructured data, like email conversations, social media posts, video content, and so on. Combining this messy and complex data with other more traditional data, like transactions, is where a lot of the value lies, but you must have a plan for the analysis.
4. How will I report and present insights? Data is useless if the key insights from that data aren’t presented to the right people in the right way, in order to help decision making. Making good use of data visualisation techniques and taking pains to highlight and display key information in a user-friendly way will help ensure that your data gets put to good use.
Keeping your target audience in mind is perhaps the most important thing to remember at this stage. So, in this step you need to define how the insights will be communicated to the information consumer or decision maker. You need to think about which format is best and how to make the insights as visual as possible. You also need to consider whether interactivity is a requirement, i.e. do the key decision makers in your business need access to interactive self-service reports and dashboards?
5. What software and hardware do I need? Following on from defining what data is needed, how it will be turned into value, and how it will be communicated to the end user, you need to define your software and hardware requirements. Is your current data storage technology right? Should it be supplemented with cloud solutions? What current analytic and reporting capabilities do you have and what do you need to get?
6. What’s the plan of action? Having identified the various needs above, you’re now ready to define an action plan that turns your data strategy into reality. Like any action plan, this will include key milestones, participants and responsibilities. After creating your data strategy, one of your first steps will be to make a robust business case for data to the people in your organisation – effectively convincing them of the merits of using data and linking the benefits back to business KPIs. Importantly, you should also identify training and development needs within the company and recognise where you might need external help.
I’ve used this six-step approach with companies and government organisations of all sorts of sizes, across many sectors. I find it a simple and intuitive method for creating a data strategy, and one that engages the key decision makers in an organisation – I hope you find it helpful, too.
In addition to these six steps I have also developed a template for developing a data strategy as well as a template for defining data use cases for your business.
There’s really no escaping artificial intelligence (AI) and the Internet of Things (IoT). It seems pretty much anything can be made smart these days – and that goes for services as well as products.[...]