The Changing Face Of Analytics In The Years Ahead

The Changing Face Of Analytics In The Years Ahead

Analytics has been around for many years and I am sure every organisation has some form of analytics in place, whether that be in the form of macro laden spreadsheets or the most sophisticated self-service visualisation solution. Like most technology in recent times, analytics has gone through some dramatic changes such as mobile becoming a reality and self-service offerings gaining traction. 

These changes have come about in order to cope with the increasing demands of the users and customers as well as the increasing volumes of data we are now faced with. The key question businesses should be asking is “what is my business doing with analytics?”. In years gone by, analytics was often an after-thought for many businesses and often seen as a trend that will pass. Today, businesses are realising that analytics is not some sort of ‘nice to have’ but absolutely fundamental to the survival of their business. If your business views analytics as a ‘nice to have’ then it is probably time for you to think again. 

Analytics will be round for many years to come and it is one area that will continue to receive a large amount of R&D spend from vendors to ensure it continues to help businesses become and remain Smart Businesses. 

Let’s take a look at some of the changes we can expect to see in this area in the years ahead:

1. Analytics for the Masses

We are all too familiar with the comment “IT is a bottleneck!” as users wait around for IT to provide the information they require, therefore delaying the decision making process. 

With the increase of self-service analytical offerings coming to market, analytics has now progressed from being an IT function into a business function. The functionality now provides the business users / decision makers with the power at their fingertips to create their own reports and carry out their own analysis without the need for technical input. We are even seeing an increase in self-service data preparation offerings coming to market to allow users to prepare their own data in an easy fashion ahead of analysing the data.

Having said the above, we are nowhere near full pervasive analytics within business, however it is on the increase as the offerings become simpler and this will continue in the years ahead especially with the increase in cloud analytical offerings. 

2. Companies will embrace Predictive and Prescriptive Analytics

The majority of companies today do what we call Descriptive analytics and this involves analysing historical data to understand what has happened in the past. This is great for confirming things you may have known but just needed the facts to back it up or to identify things that you may not have known but it is all based on what has happened.

The next step in the analytical journey is for companies to move into the realms of predictive analytics. Predictive works by analysing past data and predicting possible future outcomes based on the historical patterns. 

After predictive analytics come prescriptive analytics and this takes it one step further. Prescriptive analytics not only predicts the future it also makes recommendations on what you should do based on the prediction.

At the moment customers are starting to take the journey from descriptive to predictive analytics due to simplified predictive offerings coming to market but we will see this trend continuing into the prescriptive arena.

3. We are faced with a data tsunami

With the Internet of Things (IoT) starting to gain traction within businesses and communities along with the ever increasing use of social media, the amount and type of data we are now faced with is constantly growing and changing at a phenomenal rate.

Cisco are estimating that there will be 50 billion connected devices by 2020 with each of these devices capable of generating data. Take a minute to think how many devices you have on your person at the moment that are or could generate data. Now think of all the devices within your business that are or could be generating data and you soon realise the sheer scale of data that is out there. Now think about how you could use that data to benefit your business.

For example, think how behavioural data from social media could give you deeper insight into your customers, think how data from sensors fitted to your fleet of vehicles could give you insight into how they are being driven and identify areas where you could cut fuel consumption and ultimately save money.

Analytical solutions are now capable of analysing data from more sources and different types of data than ever before and this will only increase in the years ahead.

4. Analytics gets SMARTER and EASIER

Analytics / BI of old would involve creating a report (typically a list style report) against a relational database which contained data in a structured format (i.e. rows and columns). In today’s world the data we receive has changed dramatically and we now need to analyse data that is semi and unstructured. 

We also need to be able to analyse data in motion to ensure we can cope with the real-time demands of the users and customers. Streaming technology allows us to analyse data in real-time from sensor devices for example and working out what data it needs to persist and what data it can drop. 

We now have machine learning techniques embedded into the analytics offerings that not only reads our query but understands the context of the query, therefore making life easier for the user by removing the thinking element. 

We have analytical offerings on the market today that we can interact with using natural language to query the data, this simplifies the analysis for the end users and increases the pervasiveness of analytics throughout the business. A great example of this is IBM Watson Analytics.

Huge strides have been made in this area when it comes to analytics and this is an area that will advance in the years ahead making it even easier for non-technical decision makers to gain insight from their data. 


Many businesses today still have a very siloed approach to analytics and by this I mean, each user / department has their “own version of the truth”. Storing information in such a disparate manner makes the decision making process very difficult as you can’t get a holistic view of the data. No matter how good the analytic solution you have in place, if you can’t see the whole picture then the decisions you are making can’t be made with complete confidence.

Personally, I don’t differentiate between the data and the user experience when it comes to analytics, you need both as one without the other is only 50% of the answer. Today I still find business where employees are manually consolidating data from multiple source systems into Excel spreadsheets in order to get the more holistic view of the business they require.

Whilst this is a very time-consuming exercise, it is also highly vulnerable to human error and therefore leads to an environment where the data cannot be trusted and this often leads to incorrect decisions being made. As mentioned previously, the “data tsunami” is upon us and manually “hand cranking” data will become more difficult if not impossible in the future.

Automation is a key area that businesses need to consider when looking at getting the most from their analytics investment and creating an environment where people are working smarter not harder. Having your employees “number crunch” is delivering very little benefit to the business so you need to release them from the heavily manual tasks they undertake to produce the analysis and automate the data and analytics production.

The technology that allows us to automate key steps in the production of analytics has come on leaps and bounds in recent times and like the other topics above, this is an area that will continue to be enhanced in the future.


Our Logo

Need to use our logo? - download a higher resolution version:

If you would like more information about CSI, please see the About section or contact the Press department.