Data analytics

The data & analytics trends that business leaders need to be aware of

Data analytics has become a common term used amongst business leaders. It is a huge industry that is growing and changing all the time. The key therefore for business leaders is to understand the parts of it that are relevant to them and their businesses. Armed with this knowledge they can then employ the most appropriate and relevant strategies accordingly. With many buzz words flying around it’s possible to get caught up in the hype and to miss the point entirely. The point being that a timely executed data analytics strategy, has been shown to have a measurable impact for those business who have implemented one.

Every year over the last few years, Gartner has created a report called ‘The Top 10 Trends in Data & Analytics’. The target audience for the report is data & analytics leaders, as much of the content discusses deep technical topics. However, there are always takeaways for business leaders who would like to understand how the trends will impact them. The aim of this article is to identify the key trends from the last 2 years and explain them in lay terms.

There are 4 key trends that business leaders should be aware of :

  • The decline of business intelligence dashboards
  • A shift from big to small data
  • Engineered decision making
  • Insights on demand

We’ll discuss each of these in isolation and then explain why collectively they are significant for business leaders to not ignore.

The Decline of Business Intelligence Dashboards(Data analytics)

Recent times has seen an explosion in the number of business intelligence tools and dashboards. But like many advances in technology, there have been many tools suggesting that they are the magic solution to address all BI challenges. Every new dashboard has been the next best way for businesses to extract insights from their data. In 2018, Computing carried out research in the UK to better understand the adoption and usage of dashboards. The conclusions drawn from the research were as follows:

  • BI dashboards are failing in their key deliverable – to act as the conduit of insight. For organisations trying to progress from being driven by insight as opposed to data, they are not the solution. They are, in fact, the problem
  • “………….automated data analytics represent the evolution of data analytics into a product capable of delivering what businesses need to survive and thrive in an unforgiving business climate
  • Only automation can deliver insight continually, because live data can be analysed in the background all the time………..The result is personalised delivery of insight, to the right person at the right time – in language they can understand

In the top 10 data and analytics trends for 2020, Gartner discussed the “decline of the dashboard” as a key trend where

  • Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration. As a result, the amount of time users spend using predefined dashboards will decline

A shift from big to small data(Data analytics)

Big data is characterised by the 3 Vs :

  • Volume
  • Velocity
  • Variety

This ZDNet article provides straightforward breakdown of what this actually means. The adoption of big data into every day thinking has created a buzz and a lot of hype around it. The premise for the hype has been that organisations could gather all their data into one place. Then use machine learning algorithms to give them all the answers they need. This belief has been proven to be not only ambitious but also an unrealistic view of what is possible and needed.

Part of the solution has been to split the big data problem into smaller, much more manageable chunks. This shift is what is referred to as small data. In some instances the data is both small and wide. In their review of data and analytics trends for 2021 Gartner stated that

  • Small data, as the name implies, is able to use data models that require less data but still offer useful insights

A shift to small data also means that some of the technical challenges inherent for big data are less of a concern.

Engineered decision making

There is a new field emerging in data and analytics called decision intelligence. In order to make accurate, consistent, repeatable and traceable decisions, there needs to be a standardised way of doing this across a whole organisation. The aim of decision intelligence is to make this possible by identifying a range of human and machine based decision making approaches and grouping them into business processes.

With this in place, according to AI Multiple, the benefits provide the ability to

  • Make more accurate decisions that provide better outcomes
  • Make faster decisions
  • Eliminate errors like biases
  • Accommodate the benefits of human judgments like intuitions

Insights on demand

To enable organisations to remain competitive, insights needs to be in the hands of decision makers at the point in time that they’re relevant. So rather than relying on specialist insight teams or citizen data scientists, organisations will empower all their employees with the ability to get manually and dynamically generated insights. Gartner believes that:

  • “…….dashboards will be replaced with automated, conversational, mobile and dynamically generated insights customized to a user’s needs and delivered to their point of consumption

If you are interested in Insights on-Demand why not check out our guide to building this system within your organisation: Why top FMCGs are seeking Insights-on-Demand and the 3 Phase solution to beat them to it.


It’s clear that some organisations are overwhelmed and/or confused by the data analytics industry. The above has shown that it is possible to decipher the jargon, ignore the hype and create a data analytics strategy that will be of benefit to the whole organisation. With that, the question remains whether a company is willing to take the necessary steps to achieve it.

Please do get in touch to find out more about which trends you need to look out for in the future.

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