“Barrachd exists to help our customers uncover what they don’t

know, before it’s too late.”

From Data to AI ... using Analytics to forecast the future

Alan Crameri, Technical Director

What we do …

Data Warehousing

Core Analytics

Predictive Analytics

AI/Machine Learning

Social Media Analytics

System Agnostic

Data migration & analytics

Finance Planning

Report Automation

Financial Reporting

Statutory Reporting

Student Number Planning

Operations Planning

Dashboards

Executive Dashboards

Talent Analytics

Workforce Planning

Workload Management

Social Media Vetting

Social Media Intelligence

Stock Planning

Barrachd is a key business within Capita’s Software Division, one of the largest software and IT services suppliers in the UK

Machine/Deep Learningand AI are everywhere

Facial recognitionUnlocks your phone

Fraud detectionProtects your credit

RecommendationsHelps you shop faster

Chat BotsRoute calls quicker

Spam detectionUnclogs your inbox

Machine visionDetects cancer early

Speech recognitionLets you go hands free

Autonomous VehiclesDetects pedestrians

“75% of commercial enterprise apps will use AI by 2020.”

“Knowledge workers spend 80% of their time searching and preparing data, not on innovating with Data Science & AI.”

“85% of CIOs will be piloting AI programs by 2020.”

“Only 4% of CIOs worldwide report they have AI projects in production.”

The ‘new world’ of AI …

Gartner’s Hype Cycle for AI

AI is not Magic

“Any sufficiently advanced technology is indistinguishable from magic”Arthur C Clarke

Evolution of AI / Machine Learning

Explicit Knowledge Tacit Knowledge

‘Expert Systems’ ‘Machine Learning’

1970s Today

Need training and experience … DATA!

Knowledge Base User Interface

Inference Engine

If-then-else-rules Forward chainBackward chain

Ability to ask question get input and explainrationale for answer

The thirst for data … Training AI

The Journey to AI

Descriptive Diagnostic Predictive

Data must be the foundation

Whathappened?

Why did it happen?

What is likely

to happen?

PrescriptiveWhat action

should we take?

Most are here

The Data Landscape

Unstructured

Structured

Internal External

EMAILSURVEYSTELEPHONE CALLSCCTV

DATABASESSPREADSHEETSCSV FILESXML FILES

FACEBOOKTWITTERINSTAGRAMWIKIPEDIA

NATIONAL STATISTICSCENSUS DATAWEATHER DATAETC

5% 4%

85% 6%

How can we exploit?

Social Media Analytics

• Direct, fast and telling data set.

• Analyse:

– Seasonal trends

– Event launches

– Competitor Analysis

– Growth Analysis

– Market Share Analysis

– Product Comparisons

2.23 BILLION USERS

1 BILLION USERS

300 hours of video uploaded per minute

Message Boards

Forums

Websites

Live capture of information from 500,000+ sources

Proprietary user configurable multi-layer filtering engine developed over 8 years

Alerts surfaced in a range of formats

Search Terms Company / Asset Known Accounts Geo-Location Noise Reduction

Convert millions of data points into individual pieces of valuable intelligence

Capture Filter Surface

Email Alert

Dashboard

API

Scheduled Report

Text Message

[1 second] [1 second] [<1 second]

AI

Anglo American

BHP Billiton

Implats

AngloGold Ashanti

Collahuasi

Los Bronces

Mantoverde

Escondida

Antamina

Spence

Kibali

Tropicana

Geita

Natural Disasters

Labour Issues

Social Unrest

Mechanical Failure

Flow Disruption

Ngezi

Stocks Link to assets Monitor issues Deliver output

Geo Located Assets

Earthquake

Flood

Wage negotiation

Strike

Protest

Blockade

Collapse

Breakdown

Explosion

Spill

Alert

Iterative noise reductionprocess

How it works for mining …

Jan 24th

AM

Union says strike very likely after ‘absurd’ offer from BHP24th Jan 08:57 GMT

24th Jan 11:48 GMT

Jan 24th

PM

Wage offer rejection confirmed in English…24th Jan 17:00 GMT

… and confirmed by Reuters24th Jan 17:20 GMT

Private local account suggests probability of half strike at Escondida mine3rd Jan 21:42 GMT

Jan 3rd

Reuters LatAm suggests strike in February if negotiations do not progress4th Jan 17:49 GMT

First story in English4th Jan 18:14 GMT

Jan 4th

Strike fund set up by workers12th Jan 07:28 GMT

Strike fund confirmed by financial news provider12th Jan 10:49 GMT

Jan 12th

Jan 19th

Precedent set for Escondida at El Penon mine ($12m dollars bonus secured)19th Jan 08:54 GMT

19th Jan 11:24 GMT

Jan 13th

Benefits cut by mine-union pushes for strike13th Jan 00:52 GMT

Local news station interviews union leader live to discuss liklihood of strike13th Jan 11:37 GMT

Information Advantage

1 day advanced warning 3 months advanced warning 7 months advanced warning

The Data Landscape

Unstructured

Structured

Internal External

EMAILSURVEYSTELEPHONE CALLSCCTV

DATABASESSPREADSHEETSCSV FILESXML FILES

FACEBOOKTWITTERINSTAGRAMWIKIPEDIA

NATIONAL STATISTICSCENSUS DATAWEATHER DATAETC

5% 4%

85% 6%How can we create?

Proactive & Predictive Maintenance

REACTIVE

PERIODIC

PROACTIVE

PREDICTIVE

Fix when the equipment is down

Scheduled maintenance

Eliminate defects at an early stage

Use analytics to predict machine failures

IoT

Predictive & Proactive Maintenance

Data Integration Data StorageIoT Platform Dashboarding

o Reduce unplanned downtimeso Optimized production outputo Identify optimal equipment configurationso Improved Overall Equipment Effectiveness (OEE)o Improve operations, productivity, efficiency

Business Outcomes

Predictive & Proactive Maintenance

IBM DB2

Warehouse

Best-of-Breed approach

Data Integration Data StorageIoT Platform Dashboarding

Industrial Sensors Industrial Edge Gateways

Cellular Backhaul Connectivity

Network Infrastructure IOT Platform Analytics Machine Learning

Dashboards/Visualisation

AI-powered fire detection

2. An ‘alarm’ is triggered

1. Image with high-potential of a fire situation is detected

3. Operator makes evaluation and indicates if it’s a ‘real fire’ or ‘false alarm’

The future …

Data Scientists are a scarce resource• Diversity in skill levels• ‘Citizen data scientists’ emerging

Trends Outcomes

Enterprise data is fragmented• Moving data is costly, risky, slow• Duplication can lead to incorrect outcomes

Operationalising AI is hard• Models require constant review• Integration into engineering & support• Security, scalability, governance

Platforms to enable wider participation• Visual productivity tools• Automating data science

Multi-cloud platforms• Access to data where it is• Model training in cloud for compute power

AI Lifecycle tools• Ease & flexibility of deployment• Model management capabilities

‘Infused’ AI

A final thought …

Leverage your data to forecast the future

Make your data simple and accessible

Build a trusted analytics foundation

Progress your AI journey

barrachd.com alan.crameri@barrachd.com

Thank you