#TC18 Getting data - STAT! | Implementing Tableau at MD ... · •Dashboard = png screencap of...

Post on 05-Mar-2021

2 views 0 download

Transcript of #TC18 Getting data - STAT! | Implementing Tableau at MD ... · •Dashboard = png screencap of...

Getting data - STAT! | Implementing Tableau at MD Financial Management

Pier Martin

Assistant Vice President – Financial Analytics

MD Financial Management

# T C 1 8

Welcome

Who is MD Financial Management?• Based out of Ottawa, Canada

• 52 offices Canada-wide

• ~1,500 employees

• Over $50B in Assets under Administration

• On May 31st 2018, MD was acquired by Scotiabank for $2.59B

Who am I?Pier Martin

Assistant Vice President - Financial Analytics

Agenda• What is BI and who’s this Tableau?

• MD’s journey with Tableau

• Part I: Our Data

• Part II: Our Analysts

• Part III: Our Client-Facing Staff

• Part IV: The Hard Questions

• How far MD has come – you can do it too!

What is BI and who’s this Tableau?

Part I: Our DataData Availability & Governance

Our Data/BI Environment• SQL Server

• Tableau Server 10.5 (core-based)

• 40 developers

• 1,500 interactors

• Over 280 dashboards

When we started - Availability• Sources:

• Data warehouse via Report Builder (SSMS) – required SQL knowledge

• Excel sheets

• SPSS & statistical files

• Lack of connectivity & access levels

• You would receive an emailed spreadsheet

• Service requests for complex data

When we started - Governance• Lack of trust in source systems

• Not easy to confirm sources

• Everyone had their own “mini database” sources

• We didn’t have a quality circle – ensuring errors were fixed

• Lack of definitions of business terms and metrics

Most of allLack of faith from front-office was hurting analytics

What Tableau changedThings got more fun!

• Code-free interaction (including JOINs)

• Went from 6 specialized data ‘coders’ to 40 Tableau developers

• Visual exploration by all employees

• Direct connections to data sources –data issues were fixed at source (no patching)

• Decreased time between question and answers

Up-to-the-minute data

coverage

Live-monitoring of our data

Driving data discovery through

metadata access

Part II: Our AnalystsOur Private Trust Business

When we started – analysis• We LOVE(d) Excel

• Dashboard = png screencap of Excel

• Politics - analysts had to have contacts to get data

• Processes were manual and Excel based

• Segregated teams, multiple ‘sources of truth’

• Analytical data sets were small due to Excel limitations

What Tableau changed• Awareness of data work – audience grew

• Began to speak a common ‘data language’ (dimensions, measures, table calculations)

• Self-service, independence increased

• Sharing/repurposing work – all dashboards are shareable/reusable

• Data consolidation – “one source of the truth”

Direct-to-CRM tooltip

links = process

change from 14 clicks to

2 clicks

Live updates of progress

by case allowing for better client experience

Part III: Our Client-Facing StaffUsing Data To Drive Performance

When we started –Advisor tools• PDF/PPT and Word reports = no drill down!

• Monthly or quarterly frequency

• Siloed reports and access limitations (strict management control)

• Our staff didn’t have the ‘whole picture’ of their book of business

What Tableau Changed• Live reporting, shared to all employees

• Dynamic, interactive reporting

• Create-once, share-many

• Pull vs. push approach: data is provided and used where and when our staff needs it

Advisor coaching

tools – allows for continued improvement!

Embedded visuals mean easy access from intranet

Next actions and

client follow-up

Advisor sales against

target – self service at its

best

Part IV: The Hard QuestionsMoney, Adoption and Culture

Why should I use this?It’s not Excel!

• Learning curve & new vocabulary

• We created transparency (open data)

• Finding advocates throughout the business

• Attracting people to look at our content

Culture of Data & Information Technology

• We destroyed data silos – all work is out in the open in our Server sandbox

• Expectations went to daily/live reporting

• Data quality (push vs. pull approach)

• “If something is missing, I hear about it that day – less than 24 hours fix cycle”

• Concept of data evolved beyond “what can fit in a spreadsheet”

• Expectation is now that all results are interactive and connected

Let’s talk money• MDPT Tooltip links led to $150k year –

saving a little bit of time per user adds up!

• Tableau Server refresh– allowed us to repurpose a full time role = $80K saving

• Sales people being able to access their real-time stats without manual calculations = $330K saving(250 staff x 5mins per day = 20 hours per day = 4,400 hours per year = $330K per year)

These are only the best examples we had.. there are many more!

So.. What did our evolution look like?

How far we’ve come: 3 years ago

How far we’ve come: 1 year ago

How far we’ve come: yesterday

Please complete the

session survey from the

Session Details screen

in your TC18 app

Thank you!

#TC18

Pier MartinAssistant Vice President – Financial Analytics

Pier.Martin@cma.ca