Pythagoras was wrongDan Foreman

OKRA

All things consist of three . . . establish the triangle and the problem is two-thirds solved.

~Pythagoras

OKRA

Representation Learning Matching

Salesforce targeting

Client: Top ten biopharma companyAutomation task: Sales targetingBusiness context: Salesforce effectiveness

Sales targeting

Data: Prescription data + Activity data limited to only 6 months (3 used for learning, 3 for blind testing)Accuracy: 85% improved performance – conversion and churnProspect: High accuracy for multiple outcomes by adding more data sources

AUC = 0.86

t

True

pos

itive

rate

False positive rate

• .90-1 = excellent (A)• .80-.90 = good (B)• .70-.80 = fair (C)• .60-.70 = poor (D)• .50-.60 = fail (F)

Client: Top ten biopharma companyAutomation task: Sales targeting and messaging Business context: Sales force

GeographyHCP

Rep

Drug

8

Operates in real time Combines multiple data sources (activity,clinical,

claims, social, sales)

Creates individual eco-profiles (e.g. patient, drug,

practice, provider, geography)

Learns and understands health ecological patterns (e.g clinical, geographical

& behavioural patterns)

Spots anomalies and detects the exact moment of changes for each profile

Automates evidence generation for healthcare

and Pharma

Monitors all the profiles across all the data sources

provided

Before After

Manual rep activity planning

One-off salesforce studies, expensive and inaccurate

Time consuming studies and monthly planning

Repeated Monthly effort across

No evidence based planning

Automatic targeting and messaging,integration with CRM

Continuous and up-to-date insights

Reduced the planning time andeliminated salesforce studies

Evidence based salesforce planning

An accuracy up to 95% when moredata is used

Market research

Client: Global leader life scienceAutomation task: Social media listeningBusiness context: Launch campaign

Sales targeting

•94% detection rate of campaign related conversations and adverse event reporting

•74% reduction of time spend and manual effort by the vendor’s social listening team

•Automatic segmentation of content produced by: KOL, Patients, Caregivers and stakeholders.

•Real-time report generation instead of monthly report.

Client: Global leader life science sales and marketingAutomation task: Social listeningBusiness context: Market research

GeographyKOLs

Conversation

Source

Patient

Brand

0

0

1

1

1

1

0 0.25 0.5 0.75 1 1.25

Receiver Operating Curve for automatic social media listening

11

Operates in real time Combines multiple data sources (activity,clinical,

claims, social, sales)

Creates individual eco-profiles (e.g. patient, drug,

practice, provider, geography)

Learns and understands health ecological patterns (e.g clinical, geographical

& behavioural patterns)

Spots anomalies and detects the exact moment of changes for each profile

Automates evidence generation for healthcare

and Pharma

Monitors all the profiles across all the data sources

provided

Before After

Intensive manual social listening

High cost teams

Delays due to the manual process

Repeated effort across campaigns

Inaccurate due to human error

Automating social listening processwith a detection rate of 94%

Reducing the time spend by 74%

Reducing the volume of conversationto be manually reviewed by 76%

Allows for real-time instead ofmonthly insights

Filtering and segmentation accuracyof 94%

Other use cases

✦ Brand perception

monitoring✦ Brand attributes and

barriers tracking ✦ Parallel markets

comparison

✦ Customer insights ✦ Sentiment analyses

✦ Predicting clinical

outcome ✦ Disease parameter

ranking✦ Patient group

segmentation

✦ Patient with a disease detection

✦ Patient disease progression analysis

✦ Uplift modelling

✦ Business

intelligence ✦ Sales activity

optimisation✦ Target list

prediction

✦ Churn prediction✦ Customer bonus

automation✦ Multichannel

activity

optimisation

✦ Transaction fraud

detection and prevention

✦ Credit decision making support

✦ Social scoring

✦ Multi-source fraud detection and

prevention

OKRA real world insight

OKRA Sales & marketing support

OKRA market research OKRA Financial Services

Biometrics

13

Sync’ed to Apps

Everyday tasksMedicationCaloriesActivity levels…

Inevitable“By 2030 ML is replacing 90% of the operational tasks in an organisation.

Gartner research

Raphael AmorimAstronaut

Jeremy Howard Chief Scientist at Kaggle

Don’t take our word for it

“Thereisnoorganisationthatshouldn’tbethinkingaboutleveragingmachineintelligence,becauseeitheryoudo– inwhichcaseyou’ll

probablysurpassthecompetition– orsomebodyelsewill.”

“Yesterday we obeyed kings and bent our necks before emperors. But today we kneel only to truth, follow only beauty, and obey only love.”

― Kahlil Gibran, The Vision: Reflections on the Way of the Soul

Pythagoras was wrongDan Foreman

OKRA