The value in analysing analytics

Technologists often do technology well - but they don’t always grasp the importance of some critical aspects which drive adoption of those technologies.

As a result, technology centric initiatives often fail to live up to their full potential – and business intelligence and analytics (BI/A) is no exception. 

Of course, if important initiatives and insights are understood but not or poorly implemented they’re pointless from a value perspective.

" BI/A leaders need to better understand what drives analytics adoption (or what’s preventing it) in their organisations and take specific steps to address them.”

In essence it’s the distribution that is often lacking, not the content: BI/A leaders need to get closer to the business in order drive adoption and maximise the delivery of value.

Research like the BI Survey conducted annually by BARC and similarly by Gartner provides insight into adoption rates of BI/A over time.

What’s interesting to note is while practitioners, thought leaders, industry pundits and vendors are clear on the potential value BI/A can provide organisations, adoption rates rarely exceed half of employees (depending on the type of BI capability, size of organisation, industry, subject domain, etc.).

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If you have a higher threshold of what constitutes ‘adoption’ (i.e. more actively engaged users) the rate drops dramatically. Typically only a small percentage of users within organisations are highly engaged with BI/A – which is something you won’t see on vendors’ marketing material.

So, if business intelligence and analytics is so potentially valuable to everyone in organisations (just google the term ‘pervasive Business Intelligence’), why are so few regularly leveraging it?

Let’s start by asking ourselves a question: “how well do we understand the factors which drive adoption within our organisation?” 


As a rule these factors are not well understood or are seen as too difficult to influence by the technologists often responsible for delivering BI/A capabilities.

BI/A adoption factors within your organisation might include things like:

  • Ease of use and accessibility of BI/A (for both the toolsets and data assets);
  • Perception of the value it provides and whether it’s relevant to users’ needs;
  • Confidence in the service (i.e. opinions of performance, quality, consistency, reliability, competency of the centralised team, etc.);
  • Skills and capabilities of the user base / quality of the user training & support;
  • Cost (i.e. budgetary limitations);
  • Alignment to organisation strategy / degree of business affinity (i.e. how closely the centralised team works with the business and understands its goals and pain points);
  • Visibility (i.e. whether the service is known about / well understood); and
  • The prevailing organisational culture (i.e. whether there’s a prevailing tendency towards data driven, evidence based decision making) and levels of executive support

The above box isn’t intended to be a definitive list and will vary depending on your organisation but is intended to illustrate a point: some of these items ( mostly towards the bottom) are often not adequately understood or addressed by BI/A leaders.

Until these items are acknowledged and tackled, adoption will stagnate; and more importantly, the actual and perceived value delivered through BI/A will not meet expectations – risking further executive support and funding.


You’ll notice many of the problematic factors are not technology related but tend to fall into the ‘business’ domain. While it’s common for BI/A leaders to consider operating models, technology, architecture, processes, etc. they tend to focus less on some of the things which very much matter.

After all – for the immediate future at least – it comes down to humans and human communication and this is not always coldly logical.

This is one reason centralised BI/A teams which sit within information technology (IT) tend not to be as successful as those which sit outside of IT (i.e. within the business) – largely because IT based teams tend to have a lower degree of business ‘affinity’.

This is by no means definitive; some IT departments are exceptionally well connected to the business and partner / collaborate well.

BI/A leaders need to better understand what drives analytics adoption (or what’s preventing it) in their organisations and take specific steps to address them.

This is true even if it relates to unfamiliar and uncomfortable ‘business’ areas not traditionally tackled, such as driving cultural change in the organisation (e.g. towards data-driven, evidence-based decision making) or assisting the business in forming their strategy in a way which better leverages BI/A.

Quite simply, leaders may need to get well out of their comfort zone.

But how?

How do you do this? For leaders, leveraging in-house consulting skills to guide stakeholders through problem-solving activities aimed at identifying particular blockers to adoption is a good place to start (if stuck, consider the Problem Solving Workshop techniques advocated by the Scaled Agile Framework ).

Often, to understand these things, all we need to do is ask. As a BI/A leader, if you’ve never sat with a user and discussed what pains them, then you should do so – ASAP.  You will learn a huge amount about your offering. 

At ANZ – and this is true across organisations - we often engage with our most enthusiastic stakeholders – but you may learn much more from those who are low-level users and maybe even more from non-users. 

If asked, they will tell you exactly why they don’t leverage your service.  Sometimes the answer is painfully simple. It might be something like “there is nothing here relevant to my job” or “it’s too confusing to find the information I need and there’s little help on offer” – which is critical knowledge.

Often fresh eyes from outside can conduct a ‘health check’ style assessment focused specifically on driving adoption. But it comes back to human nature and our biggest mistake is assuming just because new technology or processes make sense people will leap to embrace them.

Michael Gibson is a senior analytics delivery lead at ANZ

The views and opinions expressed in this communication are those of the author and may not necessarily state or reflect those of ANZ.

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