Member Article

It’s Time to Trust your Data to Make Decisions

Over two thirds of those founding businesses in the past year are under 40, according to new research. Traditionally, those establishing their own brand and leading companies have decades of experience under their belt, learning from the best and building their own knowledge of what works and what doesn’t… but not anymore. So, how then have some of the world’s biggest tech brands been successfully built up from dorm rooms and flat-shares where nobody has any experience of the corporate world? And more importantly, how can you replicate that success as a young entrepreneur?

The answer is simple, inexperienced CEOs and managing directors have to trust data rather than experience to help them make informed decisions.

The Artificial Brain

The human brain is incredible. It’s said that it can store the equivalent of between 10 and 100 terabytes of data – the equivalent of more than 50 million photos. Therein lies the power of an experienced business leader: All those failures, false starts and successes have been recorded and moulded into a complex map of knowledge that they draw upon when making decisions on new situations.

It seems impossible that a simple database could match that power – but of course big data is so much more than one very large spreadsheet. One way to think about the power of big data is to consider the sum total of data held by all the big online storage and digital service companies like Google, Amazon, Microsoft and Facebook, and so on. Estimates are that the big four store at least 1,200 petabytes between them. That is 1.2 million terabytes or up to 100,000 experienced CEO brains.

The two aren’t directly comparable of course – and in an ideal world the most successful companies will combine the passion of experience with the rigour of data analytics to forge a shared path. But if you’re just relying on your own gut instincts, it’s time to consider that data can offer a much bigger picture.

Learn to Trust What You Can’t See

It’s not surprising that older business leaders haven’t immediately embraced the data revolution. There’s nothing physical to look at and assess with IT. One of my favourite scenes comes from a British sitcom where all the characters gather around a shiny black box that holds… the internet (or so they think). They easily believe that the entire internet is inside the box because it’s so hard to imagine something that doesn’t have a physical presence.

Big data is similar, but instead of a black box it’s thousands, sometimes millions, of bits of data, containing everything from your customers’ purchase history, to the current state of the investment market, through to all your financial information since founding. It’s completely unintelligible without the right tools to see and dissect the data into something manageable, then combine and investigate it into something visual or understandable.

Currently many line-of-business (or ‘everyday’) analysts understand the question they are trying to answer – but not how to get that answer. They are trying to brute-force it with spreadsheets or SQL which is leading to frustration, wasted time (where perhaps statistics and programming are not their natural skillset), and creates results that the C-suite cannot necessarily fully understand, and therefore, trust.

This is part of the reason that self-service analytics tools are currently so popular. They allow line-of-business users, such as managing directors and sales executives, to access data through a drag-and-drop, code free workflow that is easy and intuitive to use and enables them to draw back the curtain and see the results required.

Building Trust Through Accuracy

If you see a lot of yourself, or a colleague in the above, it raises the question of how you can build up that trust in your data analysis. In many cases, it comes down to ensuring the integrity and accuracy of your data, and then in the insights drawn from it. It’s easy to assume that a single mistake or missing data point means the whole set can’t be trusted. However, that isn’t necessarily true. Here are some suggestions for elements to look out for in your data to clean it and ensure that you can guarantee its usefulness:

• Accuracy – the degree to which the data agrees with the real world it is tracking
• Repetition – the removal of duplicate entities or events
• Completeness – the expected comprehensiveness of the data
• Consistency – the degree to which data across different systems agree with each other
• Integrity – the validity of a data source and its relationship to others
• Timeliness – the need for data to be up-to-date and available when expected and needed

There is no universal standard for the above. Agreement needs to be reached as to what is an acceptable level for what you are trying to achieve. However, what is important is to share the assumptions that you make along the way and to make them readily available to those interested or who could benefit from the head start you’ve provided by working on the data. Similarly, more modern analytic platforms will enable you to complete much of the above automatically, and reduce the chance of human error, and do the work without learning to code if it’s not something that you can’t do now.

Data will never completely remove the need for human experience and input into the decision-making process. However, some of the world’s largest companies have been enhanced by the power that trusting in data-led decisions gives you. So, next time you think you of know the answer, make sure to double check that all the figures agree with you.

Whilst data needs a rigorous, trusted process to get right, it is also an enormously freeing tool for the business users to draw on. There’s nothing like the thrill of hunting down the required sources, wrestling an answer out of the data, and making something amazing happen. Understanding the world better is the only way to change it!

This was posted in Bdaily's Members' News section by Alteryx UK .