By Kim Nilsson, CEO
You may have heard the news – data science is set to deliver big things for the most innovative and forward-thinking of companies. Let’s be clear – data science is going to be pivotal for steering commercial direction – no question about it. It will impact businesses in some way, shape or form and the early adopters will have a strategic advantage.
With a scramble to harness the value of data science first, businesses may be rushing headlong into what is a relatively unknown territory for them. Before so much as a data scientist is hired, questions must be asked: what is data science? How can it be applied? And what will it mean for wider business operations?
What is data science, anyway? (And do you really need it?)
At it’s core, data science is a field that uses mathematical and statistical processes to extract knowledge and insight from data. Data science is about tapping into the data that you do have, and analysing it insightfully to drive business objectives and growth. This is a fluid and multi-skilled field – a realm that merges technology, mathematics and business acumen. Without analytics, companies are in the dark about their customers, clients or users. Data science gives businesses the quantitative data they need to make better, more informed decisions and improve their services. So, do you really need it? Well, if your company is in a competitive field, and business results rely on the informed choices that everyone from the CEO to the executive makes, then yes, absolutely – data science is, without question, able to hand you a competitive edge.
How Can It Be Applied In Business? (Just Ask Netflix)
When the right strategy, the right data and the right data science talent combine, data science is capable of any number of applications. A great example of data science in action can be found at Netflix: Through tracking and analysing the behaviour of its subscribers was able to understand that their users liked programmes directed by David Fincher, that they liked actor Kevin Spacey and the British drama House of Cards had a high viewing rating. When looking at the data this showed there was an overlap of an audience who liked the same type of shows. This insight inspired the company’s decision to produce the immensely popular, award-winning American adaptation of ‘House of Cards’ starring Kevin Spacey and kicked off by David Fincher.
Also, Netflix use a recommendation engine to suggest the most relevant content based on users’ viewing history and ratings. Similar machine learning techniques are used by online retailers such as Amazon, to deliver targeted recommendations to customers based on their buying behaviour; ‘People who bought this also bought X, Y and Z.’
All of which demonstrates that the knowledge mined from data can inform the best business decisions. When done right, data science reaches every cornerstone of business and many industries can benefit from data science irrelevant of data maturity. Ways in which data science can help business depends on your drivers and business needs.
Think On – Careful Considerations Must Be Made
With the power and promise of data science, companies can and should transition to become data-driven. For the CEO’S and leaders of these businesses, this presents quite the change in role, just as being data-driven will transform a company’s culture.
This is a key part of implementing data science to businesses and making sure the insights gained are actioned. Putting this into a working example – one of the companies we worked with had 20 million sales records and using machine learning techniques were able to optimise pricing which resulted in millions of pounds worth of revenue.
This sounds great I hear you say, and yes I agree, but now there is a change that has to happen. A culture transformation within the company will be needed in order to adapt to a brand new set of operational rules, and CEO’s will quickly need to spot and capitalise upon emerging opportunities. An entire workforce – from top to bottom, will need to be advocates of change. Change is good and leaders need to inspire and encourage out the box thinking.
Top 3 Tips To Adapt To Data Science
- Organise your data You likely have stockpiled years upon years of data – now, in order to leverage data science, you’ll need it ready for processing – available to be parsed through swiftly, when and where your data scientists need it.
- Just started? No problem You may, right now, be data-less – whether owing to new business status, or lacklustre data management status. Far from being out of the game and unable to benefit from data science, you now need to do one of two things: start collecting well managed data, or purchase the data that you need.
- Get expert help Data scientists are experts in data collection, as well as executives who pose the right business questions, for targeted commercial outcomes. Team members who understand every element of the data, and who can present it coherently and visually to the wider company. Data scientists can be considered a technological hybrid professional – they merge analytical skills, with commercial acumen. By using methods such as machine learning, data mining and predictive analytics, data scientists are an asset to any business.
With the right goals set, the correct data and a healthy culture that embraces change, companies will be able to unleash the potential of data science, and in the process leap frog their competition who are yet to get to grips with all that data science can deliver.
