Our Greatest Data Hits

May 2016

Paul Lees, group chief executive [email protected]

Brian Moran, group company secretary [email protected]

Our Greatest Data Hits

Retained Surplus

£9.9m £18.3m2012 2015

Source: audited Financial Statements 2015

Annual increase in Tenant Arrears

0.07% of rent roll

£43k

Source: Mobysoft March 2016

with half the staff

Annual Void Loss

£404k0.7% of turnover

Source: March 2016 Management Accounts

Non-Emergency Repair Completion Times

7 daysmedian


Net Promoter Score - Tenants

54

Source: quarterly performance report, quart ended 31 March 2016

Net Promoter Score - Staff

47

Source: annual staff survey 2015

Development Programme 2015 - 2018

1,526 units


Housing Management Department (2008)

[THIS PAGE IS INTENTIONALLY LEFT BLANK]

Housing Management Department (2010 onwards)

What’s Going OnMarvin Gaye

10UP 6 1 YEAR IN CHART

“Oh, you know we've got to find a way To bring some understanding here today”

What’s Going OnMarvin Gaye

10UP 6 1 YEAR IN CHART

Rule association

RENT ARREARS RISK

Find the best predictor

OneR algorithm

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RENT ARREARS RISK

Find the best predictor

OneR algorithm

VIDEO DEMO

There is a link between missed gas appointments and high (>£250)

rent arrears cases

We can make sense of very large data sets

Let’s Stay TogetherAl Green

9NEW 8 MONTHS IN CHART

“Oh let's, let's stay together Lovin' you whether, whether Times are good or bad, happy or sad”

Let’s Stay TogetherAl Green


K-means clustering

Assign to cluster

K-means clustering

CUSTOMISE SERVICES & INFORMATION

AAssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssiign to cllusssssssssssssssssssssssssssssssssssssssssssssssttttttttttttttttttttttttttttttttttttttttttttttttteer

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CUSTOMISE SERVICES & INFORMATION

Assign to cluster

K-means clustering

VIDEO DEMO

We can automatically assign tenants to clusters

We can use clusters to customise services and

information

Robot RockDaft Punk


“Rock, Robot Rock Rock, Robot Rock”

Robot RockDaft Punk


Machine learning classifiers

Check web form

Naive Bayes

Classification

This new case looks like it’s of this type…

TRADE

Classification: Repairs

REPAIR REQUEST

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NaNaNaNaNaNNaNNNNNNaNaNaNaaaaaaaaaaaaaiviviivvvve eeeeeeeee ee BaBBBaBBBBaBaaaBaaaayeeyeeyeeyeeyeeyeyyyyeyeyeeeyyeyeyyyyyeyyy sssssssssssssssssssssssssss

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TRADEREPAIR

REQUESTRRREEEPPPAAAIIIRRR

RRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRREEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEESSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT

Check web form

Naive Bayes

“Our ba th room is leaking through the ceiling onto the stairs and the ceiling is wet through along with the walls where the taps are mounted. And puddle on the stairs”

PLUMBER

Check web form

Naive Bayes

Check web form

Naive Bayes

bathroomleaking

ceilingstairsceiling

wet

walls taps

stairs

PLUMBER

VIDEO DEMO

Machine learning can correctly identify trades for

70%+ of repair requests from tenants

Machine learning can support the creation of

'friction-free' self-service

I Predict A RiotThe Kaiser Chiefs

7

“I predict a riot, I predict a riot. I predict a riot, I predict a riot.”

NON-MOVER 3 YEARS IN CHART

I Predict A RiotThe Kaiser Chiefs

7

Forecasting

NON-MOVER 3 YEARS IN CHART

Forecast time series data

Holt-Winters Triple Exponential Smoothing

FFFFFFFFFFFFFFFFFFFoorrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrreeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeccccccccccccccccccccccccccccccccccccccccccaaaaaaaaaaaaaaaaaaaaasssstttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttt tttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttiiiiiiiiiiiiiiiimmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmme sssssssssssssssssssssssssssssssssssssssssssssssseeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeerrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrriiiesssssssssssssssssssssssssss dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaatttaaaaaaaaaaaaaaaaaaaaaoooorrrreeeeccccaaaaaaasssstttt ttttiiiimmmmmmeeee sssseeeerrrriiiiiiieeeessss ddddaaaattttttt

Hoolt-Wintters Triplpp eExExpoponenentntiaiall SmSmoooooththiningg

Forecast time series data

Holt-Winters Triple Exponential Smoothing

VIDEO DEMO

We can automatically identify breaks in regular

payments

We can forecast other seasonal data

What Difference Does It Make?The Smiths


“it makes none, but now you have gone,and your prejudice won't keep you warm tonight”

What Difference Does It Make?The Smiths


Randomised Controlled Trials

Test policy

RCT

No SOR provided

Detailed SOR provided

Schedule of Rates recording makes little difference to getting the repair done

We can put policy options to the test

The Times They Are A Changing Bob DylanDOWN 2 3 YEARS IN CHART

5

“Come gather 'round people Wherever you roam”

The Times They Are A Changing Bob DylanDOWN 2 3 YEARS IN CHART

5

Crowdsourcing data

"Man is the lowest-cost, 150-pound, nonlinear, all-purpose computing system which can be

mass-produced by unskilled labor."

S. Fred Singer

The Case for Man in Space, 1965

http://quoteinvestigator.com/2016/02/01/computer/#note-12956-10

Crowd sourced data

Adactus500

Apologies to XKCD: see https://xkcd.com/1235/

VIDEO DEMO

Send us a photo of your heating controls

How easy is to to use the controls?

VIDEO

We can get new forms of data from our tenants

Tenants can act as sensors

Communication BreakdownLed Zeppelin

4

“Communication BreakdownIt's always the same”

UP 5 3 YEARS IN CHART

Communication BreakdownLed Zeppelin

4

Data visualisation


Data viz

Tableau

Data vizData viz

Tableaaaaaaaaaaaaaaaaaaaaaaaaau

Data viz

Tableau

VIDEO DEMO

Risk now has a much higher profile in the boardroom

How information is presented affects the thoughts that

people have about it

Let’s Stick TogetherWilbert Harrison

3

“You ought'a make it stick together Come on, come on, let's stick together”

DOWN 1 20 YEARS IN CHART

Let’s Stick TogetherWilbert Harrison

3

SQL Joins

DOWN 1 20 YEARS IN CHART

Join existing data

SQL

Join existing data

SQL

Join existing dataJ g

SQL

SQL JOINS

Original diagrams: C. L. Moffatt, http://www.codeproject.com/Articles/33052/Visual-Representation-of-SQL-Joins

SELECT <select_list> FROM Table_A A FULL OUTER JOIN Table_B B ON A.Key = B.Key

Outer (Full) JOIN

SQL JOINS


SELECT <select_list> FROM Table_A A INNER JOIN Table_B B ON A.Key = B.Key

Inner JOINSELECT <select_list> FROM Table_A A FULL OUTER JOIN Table_B B ON A.Key = B.Key WHERE A.Key IS NULL OR B.Key IS NULL

Outer Excluding JOIN

SQL JOINS


SELECT <select_list> FROM Table_A A LEFT JOIN Table_B B ON A.Key = B.Key

Left JOINSELECT <select_list> FROM Table_A A LEFT JOIN Table_B B ON A.Key = B.Key WHERE B.Key IS NULL

Left Excluding JOIN

SQL JOINS


SELECT <select_list> FROM Table_A A RIGHT JOIN Table_B B ON A.Key = B.Key

Right JOINSELECT <select_list> FROM Table_A A RIGHT JOIN Table_B B ON A.Key = B.Key WHERE A.Key IS NULL

Right Excluding JOIN

VIDEO DEMO

We can create balanced measures of staff

performance

We can connect together many sources of data

If 6 Was 9The Jimi Hendrix Experience

2

“Now if a 6 turned out to be 9 Oh I don't mind, I don't mind”


If 6 Was 9The Jimi Hendrix Experience

2

Feature creation and engineering


Create new feature

SQL

TENANCY BALANCE

REPAIRS SPEND

RECHARGEABLE REPAIRS

ASB CASES / LEGAL ACTION

GAS NO ACCESS

COMPLAINTS

CRM CONTACTS

PARETO SCORE

Distribution of Pareto Scores

Distribution of Pareto Scores

0.7% of tenancies are challenging

Less than 1% of tenancies are challenging to manage

We can figure out ways to measure proxies for data we

don't record

SurvivorDestiny's Child

1NON-MOVER 2 YEARS IN CHART

“Even in my years to come I'm still gon be here'”

SurvivorDestiny's Child

1NON-MOVER 2 YEARS IN CHART

Survival analysis

Survival Analysis

Kaplan-Meier Estimator

S(t)=1−F(t)= Prob(T≥t)

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KaKKKaaaKaaaKaKaKKaaaaKaaKaKaKaaaaaaaKaKaaaKaaaaaaaaKaKaaaaaaKKKaaaKaKaKaaaaaaaaaaaaaplpplplpllppplplpplplplplpllppppplllllpplppllpllpppplllpllplllplplppppllpppppllpllpplplllllllpppppppllpppplp ananananaaananananaanannanananannanaaaaaanaaaaananannnnannnananaaaanaananannananaaaaaanaaanananannnanaaananaananaaaannaanaaaaaaannnnnaannaaaaannnnnnnannnaanaaaaaaaaanaaannnnnanaann-M---M-M-M-MMMMMMM-M-M-M-MMMMMMMMMM-MMMMM-M-M-MMMMMMMMMMMMMMMMMMMMMMMMM-MMMMM------MMMMM--MMMMMMMMMMMMMMMMMeieieieieieieiieieieieieieieiieieieieieiieieeeeiiiieieiieieiieeiiiiieieiieieeeeieieieieieieieieeeeeiiiiiiiiiiiiee ererereeeeereerereeerereeeeerereeeeeerereeeeeerrreeeerereeeeerererrerrereeeeeeeerrrrrrereeerrrererreeeeerer EEEstimattttttttttttttttttttttoroo

SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((((ttttttttttttttttttttttttttttttttttttttttttttt)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))===========================================111111111111111111111111111111111111111111111111111111111111111111111−−−−−−−−−−−−−−−−−−−−FFF(((ttt)))))))))))))))))))))))))))))))))))))))))))))))))))))))============================================================================================ PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooobbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb((((((((((((((((((TTT≥≥≥TTTTT ttttttttt))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))

Survival Analysis

Kaplan-Meier Estimator

S(t)=1−F(t)= Prob(T≥t)

VIDEO DEMO

Histogram of Tenancy Length (Current Tenants)

Survival Analysis can be applied to many other longitudinal data sets

Most tenancies churn quickly

Housing Association Costs

A Simple Model of Tenancy Lengths

Tenancy Length (years)


A Simple Model of Tenancy Lengths


Unlikely to need component

replacements

Likely to needcomponent replacements

Implications for Planned Maintenance

The 60:40 Rule is inefficient


Major Works & Cyclical Maintenance Spend

£888pu £679pu2012 2015

Excluding discretionary spend

Rule association

K-means clustering

Machine learning classifiers

Forecasting

Randomised Controlled Trials

Crowdsourcing data

Data visualisation

SQL Joins

Feature creation and engineering

Survival analysis

May 2016

Paul Lees, group chief executive [email protected]

Brian Moran, group company secretary [email protected]

Our Greatest Data Hits

Our Greatest Data Hits

Data & Analytics

Transcript of Our Greatest Data Hits