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Doing business in a big data world – how to up-skill and prepare for constant change

How should you prepare for a business world driven by information now available on an unprecedented scale? Cambridge MBA Lecturer in Big Data Analytics, Dr David Stillwell, has some top tips in the world of IoT, AI, dark data, quantum computing, open source, chatbots…

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What will MBAs working in management need to know?

Dr David Stillwell
Dr David Stillwell

For many in business, one of the big questions is – can you work with data people? There will be many more data scientists and analysts around in the future – both in dedicated teams and in departments across an organisation. You will need to have a good understanding of what they can do, what skills and opportunities they offer you, as well as what they can’t do – what it’s not feasible to ask them. For example, there is a lot of excitement around AI right now, but it has challenges. Voice can be turned into text by systems like Alexa, but Alexa doesn’t always understand what is being said – the gist of the conversation – like a human would. So as a future manager, you need to understand the limitations of what data science can do as well as what it offers – both in the short and long term.

What are good questions to keep in mind as a manager dealing with big data?

If you’re in a managerial role, it’s a good idea to know what questions to ask when someone is trying to sell you an algorithm. Ask questions particularly around the kinds of data they are feeding in and how it interprets it. What kinds of data would make the algorithm in question say ‘yes’ and what would make it say ‘no’? Human bias can creep in when people are designing an algorithm, or data can be used which will give a skewed response that may, for example, lead to an organisation filtering out female applicants for roles. In an instance like that the algorithm may be fed data about what characteristics a company’s top executives have and what educational backgrounds they came from. If their senior management are mainly male, the algorithm created from this data will filter out many female applicants. So ‘garbage in, garbage out’ still applies – even in this very high-tech world – and managers will be very valuable to their organisations in knowing what to look for.

What’s the main trend to look out for?

The main trend will be that big data projects won’t be stand-alone. Big data is becoming an integral part of the whole business. While it will still be vital to have specialists, such as marketers and HR professionals, everyone will have to have some knowledge of big data, and organisations are already desperate for people who can talk to both data scientists and senior management and translate one to the other. You need to be someone who can turn management priorities into something the data people can understand and offer a solution for, as well as someone who can explain the results from big data to top management, many of whom pre-date the big data era. This ability to speak the language of both worlds will be more and more crucial.

What about ethical and responsible uses of big data?

There are attempts in computer science to teach students about ethical creation of algorithms. But the people who put algorithms into practice are management. They decide which new capabilities to use and how to use them. They decide how transparent we are being with people whose data we are using and other ethical questions. These are the issues managers need to think about – not the data scientists.

When you have a big reputational issue to tackle, it is not the data scientists who will be held accountable to the public and the media, it’s the CEO and management who made the decisions around the data the organisation is exploiting. Reputational issues, of course, have implications for the bottom line, so these are serious responsibilities and management needs to understand the risks of their big data decisions.

Where does thick data meet big data?

Relying on big data alone increases the chances we’ll miss something while giving us the illusion that we know everything.

Tricia Wang, Technology Ethnographer 

Wang promotes thick data – ‘precious data from humans’ stories, emotions, interactions that can’t be quantified’. 

Big data gives organisations the chance to act like scientists and check their hypotheses against data, but it is humans who have to come up with the hypotheses to check. People generate the ideas and big data analyses them – each needs the other. The problem with human perceptions is that humans can forget things, or not be completely honest about them, and that’s where big data can help get to the heart of something.

What’s some practical prep you can do?

If you’re keen to understand big data, there are lots of online courses which will let you try some data science for yourself. Having some experience like this will be very attractive to hiring managers. Big data as a theme has a growing prominence in the Cambridge MBA curriculum, as we recognise the need to educate our future business leaders, as well as work with organisations to help them keep apace of developments.

We all need to develop a mindset of living with constant change. Data-driven projects won’t end anymore but will constantly evolve and iterate. We will be continually testing, experimenting and changing things as our customers’ and clients’ needs and desires change.

What are the future themes?

My main interest at the moment is in people analytics. How can you help managers to be better at understanding their staff and their strengths and weaknesses? How can you support HR to use big data in hiring effectively and for the success of the company?