The real value of data to your business

Posted on:

June 12th, 2020

Posted in:

Insights & Thought Leadership

As Venture Capitalist, and Author, Tomasz Tunguz once said, “the best run companies are data-driven, and this skill sets businesses apart from their competition”. Becoming data-driven takes decision-making to the next level – the 16% of businesses who use data for their key strategic initiatives (as reported by Harvard Business Review) are the ones who stand out. So, how does your company use and value its data?

Every company generates data, and most give its importance an appreciative nod, but too many still don’t get the critical role it can play in business and therefore miss out on the value it can create when used to optimise performance and power innovation. 

How much priority does your company place on using its data? You may be starting to acknowledge how useful it might be, but do you have the processes, coordination, and technologies in place to use it, and use it well? To become data driven, you must be prepared to trust your data, and make decisions based upon what it tells you about how you can improve your business performance. If you can, or would be prepared to, then you are on your way to becoming data driven; if not, then you will need to get over this hurdle first. 

Can you open your mind to new ideas?

How many times have you looked at a performance report, or dashboard, and said afterwards “well, I learned nothing different to what I suspected, but at least it has confirmed what I have always known”? Decision makers must never use the information they have available to try and prove that they are right, because if they do, the future of their company will be determined, and constrained, by beliefs from their past. The tendency to interpret new evidence as confirmation of your existing beliefs, or theories, is known as confirmation bias – and if a company is to become truly data driven, it must eradicate it.

Firstly, the data used for decision making must be accurate, complete, timely, valid, and consistent. It must also be comprehensive with nothing left out because it is deemed irrelevant. Next, the analysis of the data must include some degree of “getting uncomfortable” by looking at all sides of the issue you are trying to address, even if it means considering factors that you may have previously deemed to be irrelevant, wrong or indeed painful. It is also important to introduce opposing views. Don’t just look at the scenario with one mindset, consider it from every perspective, ensure that your thinking is based upon a 360-degree view of the matter in hand. If you ask the opinions of others, don’t just rely on your peer group, as they are mostly likely just going to agree with your approach to the analysis, or confirm that your results are correct. You must ask outsiders, people with different opinions, beliefs and different agendas to yours. Any finally, when you think you have it right, debate yourself; try to prove that you are wrong, play devil’s advocate, see if you can change your own mind. By following these steps, you can be sure, or at least a lot more confident, that you are being open minded when using your data to achieve outcomes that shape the decisions you make. 

Make it make sense

Data runs through every operational vein in your business and it is vital that you capture and use every single useable byte of it. By 2025 there will be 163 zettabytes in the global datasphere – and this can either be the asset that leads your business to success, or the pitfall that overwhelms you. Whether it becomes your cash cow or your conundrum will be determined by how well you manage and use your growing data asset. 

Every company has a vision; usually it is to be bigger, better, and stronger and to operate in ways that are supportive of communities and the environment. Supporting this vision, will be a strategy that maps out how, and when, the vision will become a reality. Do you understand how your data will support you in achieving your objectives? If not, you need to. Once you understand this, your company’s data requirements need to be built into the strategy you are following. Aligning your data requirements with your company vision and business objectives is how you create, implement and develop a data driven culture. 

As data is such a valuable resource, the more a company gathers, the better. No data should be ignored, each piece has a purpose. Imagine that you are writing a book and you have all the words ready, all you have to do is to structure them to form the plot. Ignoring any element of data would be like leaving out the words that put the twist in your story; the interesting bit, the part that makes the reader say, “I wasn’t expecting that”. 

When all data is brought together, everything and anything can be explored and minds are opened to new possibilities. This is when innovative thoughts come to the fore and when the biggest differences can be made that positively affect business performance – this is insight, this is what all companies should be striving to achieve from their data analysis.  

When you have an enterprise view of data, and you mine it for information, you begin to uncover relationships between elements that you would never have previously considered. You create meaningful patterns and trends to form the basis for insights that will change your way of thinking forever. 

Being able to analyse data in this way requires the simultaneous computation of millions of different calculations looking for patterns that mean something. Most of the time, the calculations will only prove that there is nothing meaningful to be found, but eventually, the missing links will be discovered and that’s when we get the “aha moment”; the time when we learn something new, or something different that will have a massive impact on how we think, and how we do business in the future. 

The good news is that you don’t need to sit in a dark room for weeks on end, with a calculator, paper and a pencil working through all the permutations you can think of. The deep analysis required now falls into the remit of Machine Learning. 

Machine Learning learns from data which factors are important in achieving specific goals. For example, if the goal is to improve profitability, it will learn which of the variables in-play in the data are important and why; it will also understand the relationships and work out what needs to happen so that the goal is achieved. Unlike traditional programming, the system will continue to learn as the variables change. This learning will continue to develop the computer’s thinking, expanding its experience so that it ensures the goal is met regardless of how the business evolves. Given this explanation, you begin to appreciate that today computers can learn and gain experience and begin to provide better insights. We will soon be able to rely on them to manage some key processes without human intervention; this is machine learning. 

It doesn’t need to be rocket science

When we have all the right information, analysed, and interpreted in the right way, making decisions that give a key competitive advantage becomes achievable. As Tomasz Tunguz said, “the best run companies are data-driven, and this skill sets businesses apart from their competition”. There are digitally enabled, data driven businesses operating in towns and cities all across the UK. These are the 125 who are leading the way in their chosen field; the disruptors who have changed the way business is done in their sector forever. 

Uber have based their entire business model around using data. Their algorithms automatically calculate fares, taking into account GPS and street data. As they can monitor traffic conditions, and how long a journey will take in real time, they can inform their pricing with Big Data, known as “surge pricing”. The price is adjusted to meet demand, rather than increasing prices at weekends or public holidays, it uses predictive modelling in real time. This allows Uber to make more profit as if more people are in need of a car, they will likely pay more. 

With their vast database of drivers in the cities it covers, when a passenger requests a ride Uber can instantly match them to the most suitable driver for their needs (i.e. the car size, any disabilities, the nearest driver to them) and after riding, the driver and passenger can rate each other to build up trust. Data suggested a vast number of similar journeys happened around the same time in their vehicles and Uber used this insight to develop Uber Pool, reducing the cost of riding for their passengers via car pooling, with an aim to cut London traffic by a third. This shows how Uber is data-driven – using their data to meet their customer’s needs, make more profit and make changes to their strategy.

Another example of a company using their data in a forward-thinking way is Starbucks. They have vast amounts of data from their weekly 90 million transactions, 25,000 stores and 17 million mobile app users that positions them on the cutting edge of using big data and artificial intelligence to help their sales, marketing and business decisions. Their rewards app has a further 13 million users where information about their habits is collected. From their favourite drinks, to their preferred time of day to order, even when a customer enters a new Starbucks location, they can be identified and treated like a regular. 

As well as informing the barista of the customers’ preferred order, the app can suggest complementary products and new items they may want to try. It will also take into account the weather, day of the week and which location they are in before making its recommendations. So, if the weather is particularly warm, it may suggest its Frappuccino range over its hot beverages. Its personalised offers reach out to regular customers but also those who haven’t visited in a while to re-engage them. This improves the customers’ experience, so they continue to visit Starbucks over competitors. 

Starbucks doesn’t just use data to drive its marketing and customer-centric decisions, they use and analyse data when deciding on where to open new stores – taking into account the proximity to other branches, demographics and traffic patterns. This ensures decisions are made that give the best chance of the new unit being successful.

Becoming data driven is imperative for most companies

If you want to be the champion in your industry, you need to be using your data to its full potential. Make better, and more informed decisions, come up with new innovative ideas about how your business operates and how you keep your customers engaged: become data driven like Uber and Starbucks.

At Clekt, we will help you to understand the real value of your company’s data. We will work with you to ensure that your future vision, and strategic objectives are aligned to your data management so that you succeed in your aims. We believe in the power of data and understand the strength that being data driven will add your company.