evolve your analytics platform to impact your business

Evolve Your Analytics Platform

to Impact Your Business

Chris Engstrom

Director, Advanced Analytics & Machine Learning

10/31/2018 © 2018 eCapital Advisors, LLC.

Objectives

▪ Show how integrated Machine Learning (ML) solutions

can be applied to common business problems

▪ Showcase various algorithms/methods

▪ Classification

▪ Time series forecasting

▪ Clustering / segmentation

▪ Decision optimization

▪ Connect!

© 2018 eCapital Advisors, LLC. 210/31/2018

Focused on Applied Data Science

Chris Engstrom


▪ Microsoft (8 years)

▪ Medtronic (8 years)

▪ LLC consulting (4 years)

▪ Med Tech startup

Domain Experience: Tech, Med Tech, Med Device, Sales

Finance, Healthcare, Marketing, Direct Marketing, Higher

Ed, Insurance, Sales Planning & Management

Data Math

Business

Every Client is in a Different Place

Quantitative

Applied Data Science Skills

TechnicalSkeptical

CuriousCollaborative

Motivations

▪ Excitement / Fear

▪ Leadership pressure

▪ Competitive pressure

▪ Acute needs

▪ Fast growth/decline

Barriers

▪ Confusion

▪ Where to start?

▪ Budget

▪ Leadership support

▪ Data environment

Capabilities

▪ Advanced

▪ Capable but siloed

▪ Getting there

▪ Just starting out

▪ Nowhere

Data Are Now Strategic Assets

5Source: IBM Analytics Life Cycle:

The Machine Learning market is expected

to expand from $1.4B to $8.8B by 2022

The Prescriptive Analytics market size is

expected to grow over $4.5B by 202131% CAGR

44% CAGR

▪ Data Science is happening NOW/FAST

▪ Transformational applications

▪ Not about IT. About Competitive Advantage

Data Science platform market size is

expected to grow to over $100B by 202139% CAGR


Descriptive

Analytics

AI Decision Optimization (DO)

Predictive

Analytics

Machine Learning

Cognitive Data

Science

Data

Mining

NLP


Company X

A view from Finance and

Business Analytics

Finance and Business Analytics

Strategic▪ Centerpiece of the organization

▪ Oversee entire business

▪ Strategic thinkers / relied upon

▪ Enable execution of strategy

Tactical▪ Deep understanding of data sources

▪ Responsibility to maximize assets/capital

▪ Planning and forecasting across all functions

▪ Sees things functional areas can’t (mobile example)

8

IT does not

have this

perspective

Positioned

to Drive New

Approaches

Company X Challenges

Top Problems for Finance and Analysts1. Flat revenue and irrational pricing

2. Forecast accuracy

3. High employee attrition

Related Analytical Challenges▪ Data environment largely impenetrable

▪ Result has been random self-service one-off analyses

▪ Analysis limited to Descriptive Analytics (rearview mirror)

▪ Limited understanding of customer purchase behavior

▪ Do not know true “Cost of Attrition” (COA)

▪ What correlates with employee attrition


Flat Revenue and Irrational Pricing


(Needs Attitudes Behaviors)

cluster algorithm

Customer Base

LTV = $40K

Cluster 1

Cluster 2

Cluster 3

C=1,500

LTV=$33K

C=900

LTV=$51K

C=600

LTV=$67K

“Needy Infrequents”

“Engaged Actives”

“Big Ticket Erratics”

Identify useful variance

C=3,000

Flat Revenue and Irrational Pricing


Segment Name Size

%

Order

Vol

Order

Freq

Prod

Mix

X-Sell

Rate

Upsell

Rate

Margin

%

LTV

Big Ticket

Erratics

20% Low Erratic Low Low Med High $67K

Engaged

Actives

30% Med-

High

Regular High Med Low Low-

Med

$51K

Needy

Infrequents

50% Med Erratic Med Low Low Low $33K

Segment Profile and Priorities

Results

• Improved customer

understanding

• Uncovered margin

variance and

irrational pricing

• Customized Sales

and Marketing

• Better time/resource

allocation

• Improved customer

interactions lead to

increased revenueNeedy

Actives

Big Ticket

Forecast Accuracy


Baseline ForecastsSegment

Needy

Actives

Big Ticket

Solutions

▪ Auto-reforecasts

▪ Auto-reforecasts

▪ Change detection

▪ Custom forecasts

▪ Custom reforecasts

▪ Change detection

Results

▪ Improved accuracy

▪ Improved time and resource allocation

▪ Seasonality identification

▪ Auto-forecast 10K customers or 100K SKUs

Employee Attrition

13© 2016 eCapital Advisors, LLC.

▪ Example: Voluntary employee attrition

▪ Problem: Limited HR resources

Direct Indirect

Cost of Attrition (COA) (1.5-2X Salary!)

Training costs

Onboarding costs

Recruiting costs

Relocation costs

Vacancy costs

Separation costs

Competitive risk

Customer impact

Team morale

Lost knowledge

Team productivity

Position productivity

Scheduling

Nightmare

Dynamic Dashboard

14

ID Months

Tenure

Employee

Title

Employee

Manager

Alignment

Risk

Engagement

Risk

Performance

Risk

Manager

Risk

Commute

Distance

Other

Risk

Attrition

Risk

Training

Investment

Business

Impact

65837493 4 Title 1 M. Shetland High NA Low High High High 0.90 $2,000 Low

72682738 45 Title 2 J. Barr High High High High High Low 0.81 $41,000 High

92840193 34 Title 2 J. Barr High Med Med High Low Med 0.78 $32,000 High

89283920 2 Title 3 S. Malevich Low NA Med High Med High 0.78 $1,000 Med

19201846 17 Title 1 P. Gupta High Med Low Med High High 0.77 $2,000 Low

85027292 53 Title 3 L. Stevens Low High High Low Med Med 0.75 $25,000 High

91802893 71 Title 4 K. Malik Low High Med Low Med High 0.74 $22,000 Med

.. . . . . . . . . . . . .

.. . . . . . . . . . . . .

.. . . . . . . . . . . . .

81034692 52 Title 4 F. Dolan Low Low Low Low Low Low 8% $43,000 High

23625272 34 Title 5 S. Adams Low Med Low Low Med Low 0.08 $28,000 Low

46736383 29 Title 2 K. Boyd Low Low Low Low Low Low 0.07 $23,000 Med

62835739 44 Title 2 Y. Zulan Low Med Low Med Low Low 0.06 $32,000 Low

72916829 62 Title 5 X. Zhang Low Low Low Low Low Med 0.06 $37,000 High

38399101 55 Title 4 S. Adams Med Low Low Low Low Low 0.06 $74,000 High

78378379 63 Title 4 R. Haloran Low Med Low Med Low Low 0.05 $38,000 Med

Predictive Category

(employee subgroup = 612)

Decision FactorsEmployee

Drill into each

employee record for

a detailed risk profile

Employees with High Alignment Risk are

in roles or on teams that do not maximize

their passion, skills, and experience.

Employees who have low tenure with a

manager or are working for a difficult manager

can be at very high risk of voluntary attrition.

Commute Distance can have a

profound impact on attrition.

© 2016 eCapital Advisors, LLC.

At-Risk Employee Interventions


Assumptions▪ 1,000 employees▪ $80,000 annul salary▪ Cost of Attrition = 2X salary

It All Begins and Ends with

Actionable Data

16

Customer Transactions

Modern Data Platform

Customer Support

Decision Optimization

Engine

Marketing Analytics

Digital / Social Media

Predictive Attrition

Modeling

Time Series Forecasts

Actionable Insight

Etc. Advanced Analytics

DATA INSIGHT $VALUE

RESULTS

eCapital FastStart Approach

17

Focus▪ ROI (true need)▪ ROI measurability▪ Deployability▪ (13 factors)▪ (readiness factors)

Project Candidates

Critical Success Factors

Smart Project Selection FastStart Development1 2

▪ Phased Roadmaps

▪ Rope Bridge approach

▪ Get data and get going

▪ Parallel IT/DS Roadmaps

IT Development

Predictive Analytics Roadmap

Deployment

Next Steps


✓ Connect on LinkedIN

✓ Continue the discussion

Chris Engstrom


https://www.linkedin.com/in/chrisengstrom

[email protected]

mailto:[email protected]


APPENDIX

Employee Attrition is A Serious Issue

20Source: Chief Human Resources Officer insights from the IBM C-suite Study. This report draws upon input from the 4,183 CxOs we interviewed as part of IBM’s first study of the entire C-suite. It

is the 17th in the ongoing series of C-suite studies developed by the IBM Institute for Business Value. We now have data from more than 23,000 interviews stretching back to 2003.

Only 13% of Organizations Predict Attrition

21Source: Chief Human Resources Officer insights from the IBM C-suite Study. This report draws upon input from the 4,183 CxOs we interviewed as part of IBM’s first study of the entire C-suite. It

is the 17th in the ongoing series of C-suite studies developed by the IBM Institute for Business Value. We now have data from more than 23,000 interviews stretching back to 2003.

Cost of Attrition of a Single Employee is

1.5-2X Salary!


Source: https://www.linkedin.com/pulse/20130816200159-131079-employee-retention-now-a-big-issue-why-the-tide-has-turned/?irgwc=1

Model Improvement Results

23

31%

61%

93%

10

20% of the employee file

contains 61% of employees

with highest risk scores.

Top 10% of employee file

contains the 31% of employees

with highest risk scores.

%%

© 2016 eCapital Advisors, LLC.

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