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Big Data, Artificial Intelligence and Business Intelligence – what’s the common currency?

PI > (Data x (AI + BI))

Big Data, Artificial Intelligence (AI) and Business Intelligence (BI): all big news in recent years. The common thought is that all we need is more data, super-smart data scientists and self-serve always-on dashboards and everything will miraculously fall into place. Right? Not quite. Sorry to burst the big data bubble, but I suggest there are a few important details missing…

Before I explain let’s look at what these things are;

  • What is Big Data – Massive amounts of data from multiple sources that flows through organisations. If tamed, and used appropriately, it could be useful and valuable for achieving desired business outcomes.
  • What is Artificial Intelligence (AI) – Intelligence driven by machines using data inputs as opposed to the natural intelligence that humans exhibit. Depending on the definition you subscribe to, AI covers everything from simple data analysis through to robot ‘brains’.  Whether intelligence of the artificial variety or natural variety is superior depends very much on context (inputs and application). But that’s a discussion for another day.
  • What is Business Intelligence (BI) – This has been around since the dawn of business. Excel sheets have supported BI in big business for decades and preceded the adoption of self-serve digital technologies (and they still do for many). The modern wave of BI tools enables self-serve reporting and insight in real-time which, if done well, can drive significant operational efficiencies. In other words, they can make people’s lives easier.

Data serves both AI and BI. The outputs of these serve strategy, marketing and operations – to name just a few important decision-making functions. Raw source data tends to be reshaped in different ways to serve different functions, however, resulting in the starting points for conversations often using multiple base definitions. As such, reaching a common understanding or internal alignment can be more challenging than it should be. To use a workplace cliché, people wouldn’t be singing from the same hymn sheet.

So, whilst data is a common asset used across business functions there is often not a common currency to bind strategic conversations. Clearly defined business actions, with targets and post implementation reviews of those actions, should be a straightforward exercise. Volume and value metrics do generally feature but they do not help contextualise the activation of a strategy i.e. the directive of ‘get more and do it quickly!’ is (spoiler alert) just not a long-term success strategy.

In a typical business, long lasting success is achieved by affordably delivering a brand value proposition which attracts profitable customers who remain loyal and ideally advocate it to others. Staff members’ understanding of their role, skillset, motivation and retention is central to delivering success. This all needs robust planning, measurement and ongoing refinement to ensure the people working in the business adapt their behaviours and outcomes successfully to an ever-changing business landscape.  There have been many recent examples of large employers with many customers who have failed to adapt and have died…don’t be one of those! R.I.P Blockbuster and Toys ‘R’ Us.

Building the appropriate tech stack can be complex, but the single biggest challenge in large organisations is to get everyone working towards the same outcomes in an effective way. We need to be able to find a simple ‘language’ to direct business that is understood across all functional areas and at all levels of staff. That hymn sheet I mentioned earlier? Very important.

This common currency which binds conversations between strategy, value proposition, AI, activity plans (marketing and operations), HR and BI however is simple – it’s people! People are what drive value in any business. These people are staff and customers. Without staff or customers, businesses are not businesses.   

To de-risk the future, and secure long-lasting success, it is critical for businesses, particularly large organisations, to implement People Intelligence (PI) in all corners of their operation. Organisations who are most ‘People Intelligent’ will win in today’s flexible digital ecosystem where people have more control over their own destiny than ever before.

Some may call this customer centricity – and they’re right to an extent – but I feel this is somewhat missing the point. Some customer-centric organisations can be over-committed to customers at the expense of staff which is not a sustainable model. That old adage ‘the customer is always right’ cannot exist without the necessary opposite ‘the employee is always wrong’ – and that’s no way to run a company. Happy, aligned staff are better at reacting to and serving customers.

Imagine with a single source of data and a common currency of ‘people’ used in all conversations how much easier it would be to drive business value;

  • Strategy is articulated using a people context for both staff and consumer matters
  • BI reports contain metrics fully aligned with the people-based objectives of the strategy
  • AI is centred on people – the lens through which statistical analysis is undertaken is always people centric (user/customer/consumer) and directly aligned with our people-based KPIs
  • Tactical marketing activities are underpinned by people-level AI
  • Brand experiences are designed for the people they are targeting
  • Operations are informed by staff-based service metrics, customer-level demand and outcomes
  • Recruitment and staff development plans are described around people-based needs
  • Internal comms provides a wrapper that consistently ties the people-centric culture of the organisation together

In short, if the purpose of your business is in any way dependent on people, you need People Intelligence. PI is much more powerful than the combination of data, AI + BI; power to the people, as they say!

Do you have a PI strategy for 2020?