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Data analytics: why it’s crunch time for your business

Your business needs analytics, but get it wrong and the consequences could be dire, says Dr Stella Pachidi, ahead of her webinar on the subject on 24 May.

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Dr Stella Pachidi

Dr Stella Pachidi

Data analytics – some swear by it, others just swear at it. Which will you be? It all depends on how the analytics is introduced. In fact, Dr Stella Pachidi, Lecturer in Information Systems at Cambridge Judge Business School, says that the way analytics is brought into a company can help make or break that organisation.

Imagine you’re a sales manager, for example, generating your own sales leads via contacts and relationships you have built up over many years. You know your patch, you know your customers. But when HQ announces that their data analysts know better than you – people who haven’t ever been near your customers, using systems that crunch the numbers apparently without fear of the consequences – tensions arise. It’s no wonder that the introduction of analytics can go badly wrong.

“It does often lead to clashes,” says Dr Pachidi. “Account managers, for example, have a lot of knowledge and experience which they apply intuitively, while assessing the consequences of their choices. That conflicts with the analyst who applies everything based entirely on data. It leads to a clash of fundamentally different world views on what kind of knowledge matters and how this should be obtained, which cannot be easily reconciled. I have observed that analytics appears to prevail over the more relationship-based approaches of sales employees, which often become obsolete, without, however, realising the pragmatic consequences for the sales practice.”

The dynamics in an organisation can add to the tension, particularly when analysts use data-based models to introduce new work practices. “Conflicts emerge – and for several reasons,” continues Dr Pachidi. “There are issues with data management, such as when there are a lot of legacy systems, or different databases, or when it is unclear who owns the data, or when it is not possible to access the right data. Staff may also have problems with accepting a data-driven decision-making culture, and then there’s the power dynamic – the introduction of data-led working may even make some functions obsolete. Finally, and very significantly, there’s simply resistance to change because of inertia – especially with IT, often people are resistant to introduce a new technology in their work.”

Which is why those who swear by data analytics need skills beyond the number-crunching. “The data scientists need to work closely with business managers, IT employees and other organisational members, in order to understand the needs and the particularities of each situation,” says Dr Pachidi. “I would say the role of a data scientist is quite demanding: excelling in analytical skills is certainly a prerequisite, but being able to speak in a language that different functions can understand is absolutely vital to ensure that analytics will be positively received and successfully implemented.”

These challenges are the theme of Dr Pachidi’s upcoming webinar: Crunching the Numbers: Introducing Analytics in Your Organisation. Among topics to be discussed are the steps organisations need to take to be ready for the potential fallout of introducing analytics.

“Organisations have more data than ever before, and across so many different platforms,” she says. “They want to make the best use of it, and they know that big data without analytics is not that useful. But introducing analytics to an organisation does take management skill.”

Communication is key. The analysts have to put substantial effort into understanding the business processes and the particular ways of working of the people involved in those processes, in order to enhance the processes rather than just replace them. It’s the analysts’ – and the management’s – job to ensure employees see the benefit of it and become committed to applying it.

“There are lessons to be learned about introducing data analytics into an organisation,” she adds. “But big data is here to stay, and the more businesses learn about how to use it, the better they’ll get at doing so – and the more effective their organisations will become.”