People First - Why Data Science is more about People than Platforms

Posted 2017-03-27T Posted by Tom


By Jason Muller, COO



The implementation of a data science strategy offers the potential for businesses to develop a deep understanding of their full data universe (customers, clients, products and platforms) and their own prospects. The growth in the data science platform market (projected to reach $101 Billion by 2021) supports the notion that businesses are aware of the advantage this level of business knowledge brings to their operations. Data science combined with technological advancements and the sky's the limit for knowledge, information and understanding. Noted research business Forrester have undertaken research that shows companies that utilise data science platforms far surpass their competitors who do not make use of the technology. However, it’s crucial for a business to understand that they will only tap into this advantage if they see data science as a holistic strategy, not just a tech system or platform plug-in. Specifically it’s about ensuring you have access to the right people first, the right platform second.



Effective Data Science Means People First



Whilst it is encouraging to see that data science platforms are well established and their value is becoming more recognised, it is important to realise that to successfully implement a platform, a business needs to cement the right people in important positions. Data science technology relies on a ‘people first’ philosophy and this means:

• Buy-in from C-suite and leadership team

• The right people to work with the systems (or the outsourcing of data scientist resource to appropriately qualified firms)

• A solid data science platforms, recommended by expert users.

That is to say that even with the best data science platform, the success of implementation and results comes from the people and so it is essential that businesses have the best resources in place before they consider the technology. To do this effectively requires buy-in from the leadership team, providing the budget for a team of data scientists, be it in-house or outsourced. It is the job of the data scientists to understand the needs of the business and seek out appropriate data and present this in usable and clear results to the company. Once a firm has the involvement, understanding and enthusiasm of its people for data science, the technology and platform marries into the heart of the business mission with ease and anticipation.



Data Science Platforms Have Established Value… With The Right Drivers



The evolution of data science platforms has been one of the most steady and progressive technological developments, proving this to be a valid and worthwhile consideration. In fact, it is widely acknowledged that technology has only recently caught up with demand in this area and that the hunger for data science is encouraging platform engineers to rapidly develop their models to maintain the pace. The Forrester Study concludes that the adoption of data science platforms throughout business is likely to double in the next two years alone - a reflection of the investment and importance of this field.

There’s a risk that businesses see data science platforms as simple ‘plug and play’ solutions; a new piece of tech on which to hand over to your business intelligence teams. There’s no doubt that the business would get extra value from this. In simple terms, it would take your business from version 1.0 to version 1.2. However, those businesses looking to take things to the next level, need the specific skills of trained data scientists to:

• Apply the scientific method to research industry and business questions

• Leverage large volumes of data from internal and external sources to answer such questions

• Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modelling

• Explore and examine data to find hidden patterns

• Present actionable insight to the business that gives them a clear competitive advantage.

Data Science platforms alone cannot do this.



Do Results Warrant Investment?



The level of investment required in these processes may initially be off-putting, however it is possible to outsource much of this resourcing to manage costs in the short term. In doing so it’s vital that businesses recognise the vulnerabilities of outsourcing to rogue traders. Some self named ‘data scientists’ are lacking in expertise and knowledge in statistical and analytical understanding and introducing such people to your business can quickly do more harm than good. Employing the expert knowledge of true data scientists ensure that your business benefits from experts who recognise how to develop models that support and enhance your business and utilises data science to it’s best ability.

The businesses that will realise the huge value that data science can add to their business, will be the ones that recognise that it is investment in people first, and not simply plugging in another analytics tool, that will give them the step-change they are looking for.

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