About the Lab

The Anomaly42 Lab is the source of all of our innovation and as such has driven the creation of our methods, our platforms and our applications, including our Sense-and-Respond Measurement and Maturity Model™ and the Enterprise Value Management suite of applications.

On launch the objective of the Lab was to aid the transition from a traditional consultancy model to one in which revenues could be driven by intellectual property. The Innovation Timeline below takes you from inception to the latest Lab developments.

Follow Freddie McMahon on twitter

Innovation timeline

January 2014: Anomaly42 pioneering the next generation of Intangible Measures for AML (Anti-money laundering)

December 2013: Anomaly42 team pioneers usig public sourced data to find new systemic failings in the sub-prime lending market

November 2013: Anomaly42 wins Salesforce.com "Most Innovative Company - Innovation Challenge, Rising Start 2014"

FusionExperience launches its Paper to Data service using Anomaly42 watch the video http://youtu.be/XwMsvcQD6eU

August 2013: We automate producing Treating Customers Fairly intangible measurements for revenue growth and reduced compliance costs.

#Anomaly42 Finding anomalies within unstructured data increases revenues and product innovation, whilst reducing cost and risks.

#Anomaly42 Intangible measurements cover all business metrics outside those that are used to measure financial and physical assets.

#Anomaly42 Intangible measurements are driven by business and regulatory imperatives - the 1# metric is Treating Customer Fairly.

May 2013: We are working on a new proposition for federating Big Data and using algorithms to deliver Smart Data for informed, timely decisions... our initial service offering will be for the consumer insurance market in the UK.

May 2013: IBM's face-to-face interviews with over 1,700 CEOs has shown a strong emergent demand for leadership through connections.. another validation of our work.. read more

April 2013: We are all aware that unexpected risks within the Financial Services sector is increasing. To learn how we are pioneering in this area read more

March 2013: Salesforce.com has agreed to start the review process for the approval of our new AppExchange app. The new app is called Fractal Maps from Sales Cloud and is expected to launch by the end of June. This is the third app aligned with our Sense-and-Respond Maturity and Measurement Model. Find out more here.

March 2013: Freddie has been evangelising why 50+ years of Data Engineering is failing. Here's the scorecard: 1) data integration has got worse; 2) data quality has got worse; 3) and the most important point of them all - business people are really struggling to understand their business data in the context of their ever changing needs.

February 2013: Freddie presented moving Beyond Big Data to Connected Small Data. Salesforce.com launched a video that shows why Connected Small Data is important - watch the way different Data Elements are 'strung together' here.

February 2013: Freddie presented at EuroCloud business transformation. This included the first public announcement that we need to rethink data towards understanding. Understanding Data Ecosystems (structured and unstructured data). View his presentation here.

January 2013: Launch of Building Data Ecosystems - see panel for further.

Read more: Innovation timeline pre-2013

Why the focus on data?

The evidence speaks for itself, the business landscape is being shaped by data as never before… Countless surveys and journal papers provide more and more evidence that successful companies ignore the significance of data at their peril.

“A common theme emerges in conversations with senior executives about their data challenges - they need real-time understanding of all data to enable effective, timely decisions to be made.“
Freddie McMahon

Freddie's thought leadership activities centre around gaining Better Control for Unknown Risks and Building Data Ecosystems. A Data Ecosystem represents the captured living nature of structured and unstructured data in context to business imperatives. Within a Data Ecosystem, the smallest elements of data are loosely coupled together through continual interaction, free flowing interrelationships, degrees of separation, data flows and timelines.