Business Analytics Blog

Business Analytics Blog

Opinions expressed on this blog reflect the writer’s views and not the position of the Capgemini Group

The ultimate data driven organisation: centralise data, decentralise analytics

Data is at the heart of digital transformation. It has climbed to the top of the agenda for organisations trying to survive and thrive in today's digital economy. Executives are starting to realise the transformative effects data has in breeding innovation, optimising operations and building customer relationships.

However, unravelling the complexities of Big Data and extracting value from information sparks a major headache for corporations who wish to pursue the oasis of an effective data driven ecosystem. To address this conundrum, we believe there are four core components of a data driven organisation.

Data capture

The ubiquity and volume of unstructured data from various sources leads to the first impediment many organisations face. There is tremendous amount of untapped value still locked away in internal and external sources of data to uncover new insights, and help companies make better-informed decisions.

Start-up giant Uber capitalises on a variety of resources to support their algorithms on dynamic pricing and enhance the user experience. Customer, geo-location and street data reveal the locations of the nearest Uber vehicle, map customers to drivers and diminish unfulfilled request. The ‘ride-sharing’ service also generates value from smartphone gyrometer data to track how fast their drivers are travelling and extract rating statistics to help maintain trust and enforce high standard between all parties.

Bigger and broader data provide organisations with enhanced panoramic and detailed views of the business, however fully integrating these pipelines often take some time. Business leaders can address short-term data needs by prioritizing requirements and identifying what sources needs to be ingested first.

Data acquisition

Businesses are burdened by legacy IT structures that hinder the ability to source, store and analyse new types of data.  

Enterprises want effective ways to combine disconnected data into synthesized knowledge about customers, employees and operations in order to achieve better results.

To do this, they need to bring together data across the business, breaking down organisational siloes to create a reliable, compliant & coherent cross functional data foundation. Centralising your data to a single repository not only unlocks insights from disparate sources, but also addresses inefficiencies such as multiple versions of the truth and spend duplication.

Depending on the size and maturity of the organisation, there are now flexible delivery models to help harness this wealth of information at a more cost effective and efficient way, from the Data Warehouse all the way to the Cloud.

Data exploitation

Companies cannot assume one technology or model today will be the best in six months time.

There is a particular focus on latency and delivering insights to end users in the timeliest manner possible. However, there are some business questions that cannot be answered straight away and require further interrogation.

Data labs provide an environment for continuous experimentation and exploration, and enables users to scan and experiment vast amounts of information to find specific answers. The key enablers here are data scientists, who will use their quantitative and computer science skills to transform huge mountains of data into new insights.

Business operations

A mature analytics ecosystem caters for all stakeholders who wish to use analytics to improve business processes.

The ‘Empowered User’ model provides an environment that allows all employees to quickly obtain insights that detail their information needs and help yields better decisions. There are four characteristics in my eyes, which highlight a best in class Empowered User organisation:

  • Self Service Analytics enables business users to access and work with data without the need for an advanced analytical or technical background.

Self-service capabilities eliminate the traditional bottlenecks associated with IT and encourage all employees to perform queries and generate reports on their own.

  • Access Anywhere Analytics provides business users access to insights from virtually anywhere and from any type of device. 

Analytics anywhere is not limited to only viewing data but also providing the ability to manipulate data from any device.

  • Work Flow Automation embeds analytics across the organisation’s processes and automates decision making through business rules.

Orchestrate and automate logical repeatable tasks and enable your digital workforce to focus on more productive tasks to help the business grow.

  • Event Management allows users to ‘manage by exception’ scenarios through reports and alerts when extreme or unusual activities occurs.

To stay ahead of the digital curve, organisations need the ability to pull, probe and distil data from all perspectives. Executives need to understand how their organisation can harness and exploit data but in turn understand how they can fully leverage their most important resource, their workforce.

 To enable all levels of an organisation to take fast and informed decisions, businesses need to centralise their data but decentralise their Analytics. Only then, can an organisation be truly driven by data.

 

About the author

Darren Hariharasegaran
Darren Hariharasegaran
Darren is an experienced Data Science specialist with a proven track record of driving business innovation across a range of sectors using advanced analytics. My areas of specialisation include Big Data Transformations, Analytics Strategy and Data Science.

Leave a comment

Your email address will not be published. Required fields are marked *.