Deriving Value From Data

May 23, 2018 8:09 am | Posted by Claire Blair

With the advent of increasing digitization and the escalating amounts of data being stored, companies face two major challenges. The first is how to manage this data growth and maintain its integrity in a secure fashion, the second is how to leverage that data to gain new competitive advantage before your competitor does.

Top Down, Bottom Up Approach

Before a major investment is made, two of the fundamental challenges that face companies ifs finding a business case to justify investment and then proving the business case before substantial investment. From a business perspective, frustration occurs when data is not available or of the right analytical capability to justify investment and colleagues in IT prefer if business requirements are pre-validated and proven before significant IT resources are expended to support. ESP acts in the intersection of business and wider organization data teams to align requirements and optimize investment.

Strategy Assessment & Delivery

Prior to delivering a data analytics master plan, it is necessary to conduct a data analytics maturity discovery and strategy assessment across 5 key areas:

  • Data and Analytics Strategy
  • IT Maturity
  • Organizational Maturity
  • Analytics Usage
  • Analytics Architecture

Video: Data Analytics & The Digital Plant – Introduction

Video: Data Analytics & The Digital Plant – ESP’s Approach


Information gleaned from our discovery stage outlines the maturity and business objectives of the different business groups. Our assessment will present possible analytics solutions for the business based on best in class industry best practices and will recommend the appropriate actions to be taken to reach state of the art status.

Innovation Workshops

ESP Innovation Workshops focus on the key business cases of interest to our customers. The workshops are customized for each customer where we facilitate the brainstorming and distilling of ideas within the customer teams. This exercise produces a prioritized list of key analytic use cases to be proven, a specification of the type of data required to prove that case (s) and a list of next steps.

Innovation Labs

Innovation Labs look at the data a customer has access to related to each specific data analytics use case on an individual basis to deliver an analysis for each business question/case of interest. It includes an analysis of the data’s quality and structure and ability to be used for business diagnostic and predictive purposes and fundamentally it’s ability to aid data-driven business decisions.


Proven Use CasesData Analytics Proven Use Cases

Production Implementations

Production Implementation of the analytics models derived in an innovation lab is then usable in a production setting in scoring real time data and providing ongoing analytic insights. ESP work with a number of leading analytic system providers in the market as well as open source software. Production Implementation is augmented with best practice model maintenance guidance, processes and systems.

About Dave Clarke

Senior Consultant/Data Scientist

Dave is a highly accomplished Big Data Analytics specialist with 25 years experience in technology – delivering information application solutions in data analytics, data warehousing, business intelligence and information management. He is an innovate team leader, skilled in multiple Big Data Analytics across manufacturing, retail, utilities, telco, healthcare, banking and insurance.




*Source: The Internet of Things: Mapping The Value Beyond the Hype, McKinsey 2015
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