Why speed and agility is important to your analytics

Agility is firmly established as one of the important attributes of modern, digital businesses.

On the Econsultancy blog we often discuss agility as it relates to marketing teams and business structures, but the concept can also have a transformative affect on data and analytics systems.

By David Moth February 23rd 2015 17:53

In recent weeks I’ve looked at why speed is so important in analytics, including analysis of five of the habits of speed-driven organisations.

These are:

Blending of traditional and new components.
Use of real-time data processing and analysis.
Analysis of diverse datasets.
Integrating digital and process transformations.
Embedding analytics within business processes.

Agility is strongly related to speed in analytics as you can’t really have one without the other, and in this post I’ll take a look at the benefits of agile analytics.

And if you want to learn more about this topic, you should attend the Econsultancy and IBM BusinessConnect 2015 interactive roundtables in March, hosted in Malaysia, Thailand and Singapore.

Agility in analytics

A new IBM white paper identified the characteristics that allow businesses to use speed in analytics as a competitive advantage.

It found that the components that differentiate organizations most are those capable of creating an agile and flexible infrastructure, one designed to manage data efficiently and move it through the analytics process quickly.

Organizations using big data technologies broadly throughout their business functions – capabilities that enable business functions to consume the data rather than just absorb it – are creating the greatest impacts on business performance.

In fact, agility and flexibility within the data architecture is a key speed-enabling characteristic.

Characteristics of businesses with advanced data capabilities (front runners) vs. those with normal or poor analytics

This requires businesses to develop solutions that support data diversity by supporting a wide variety of data and focusing on agility rather than conformity.

Landing platforms and data lakes must be built that can ingest information quickly and stash it until it’s needed.

To accelerate speed to action, it’s always better to use the structured, unstructured and unformatted data together.

And to show what this means in practice, here is a case study from a business using agile analytics.

Case study

A B2B distributor of electrical industrial supplies, Rexel UK Ltd., transformed its business strategy to place a greater emphasis on the customer experience.

To support this new strategy, known as ‘Energy in Motion’, Rexel also had to transform its approach to business analytics.

The company rebuilt its business intelligence platform from the ground up, developing an agile environment that is closely aligned with user needs. Previously, many employees were overwhelmed by the sheer volume of reports on the system and didn’t have time to utilize all the information.

Rexel transformed its reporting processes, trimming the number of reports by 90% though the use of techniques such as dashboards.

Decision makers can now access highly meaningful, on-time information in a format that is easy to understand.

According to Simon Short, head of business intelligence for Rexel:

Now it’s quick and easy for users to drill down to the relevant areas and get the information they need. Instead of spending hours in front of a screen, they’re in and out in minutes, and spending more time doing what they’re paid to, which is selling products and interacting with customers on the shop floor.

To request for your exclusive invite to attend the Econsultancy/IBM BusinessConnect 2015 events, sign up here:

> Kuala Lumpur, Malaysia (10 March 2015, Tuesday)

> Bangkok, Thailand (12 March 2015, Thursday)

> Singapore (13 March 2015, Friday)