Data Driven Business Models-GE - · PDF file4/28/14 1 Ikhlaq&Sidhu,&contentauthor& Ikhlaq...

4/28/14

1

Ikhlaq Sidhu, content author

Ikhlaq Sidhu !Chief Scientist & Founding Director, Center for Entrepreneurship & Technology!Faculty Director, Engineering Leadership Professional Program (ELPP) !IEOR Emerging Area Professor UC Berkeley

Data Driven Business Models!Berkeley Method of Entrepreneurship


Some Background at UC Berkeley Since 2000: Engineering Advisory Boards input to Dean:

“Add leadership, breadth, innovation skills, combine multiple disciplines.

2005: Innovate, Lead, ProducDze in a global economy

2011: Engineering Leadership for Silicon Valley Firms Firms: Google, VMware, NetApp, Cisco, Yahoo!, Samsung and other.

2008-‐11: Fung InsDtute for Engineering Leadership

2012: SkyDeck Accelerator

4/28/14

2


Challenge Lab

Need

Source

Externally Set

Self Originated

Societal Industry or Market

Big Data Challenge Thailand Neonatal Incubator

Mobile Applications Course Projects in Clean Energy, Education, Poverty Alleviation, Transportation …

CompeDDon Crowd-‐sourced AdaptaDon Model


Quick Outline

•  Understanding Data-‐driven Business Models

•  Key elements of every data driven business applicaDons

•  Strategic value to firms

•  Related issues: lean models and entrepreneurship

•  Besides algorithms, psychology and mindset are also necessary

4/28/14

3


Case: How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did -‐ Kashmir Hill, Forbes

•  Father to Target Customer Service: “My daughter got this in the mail!” he said. “She’s sDll in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

•  Later:

•  Father on phone: On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some acDviDes in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”


Case: Target Measurement Process

•  Target assigns every customer a Guest ID number: –  Tied to credit card, name, or email address, and any

demographic informaDon (bought or collected) –  Bucket that stores a history of everything they’ve bought

•  Assignment: Find the unique moments in consumers’ lives when their shopping habits become parDcularly flexible. (Alan Andreasen UCLA Study)

•  Target assigns: “pregnancy predicDon score,” with an

esDmate of the due date, so that coupons can be Dmed to the right stage of pregnancy.

4/28/14

4


Case: How Does Target Know-‐ Kashmir Hill, Forbes

Hypothesis-‐based model formaDon: •  NoDced: that women on the baby registry were buying larger

quanDDes of unscented loDon around the beginning of their second trimester.

•  First 20 weeks: supplements like calcium, magnesium and zinc. Also, soap and cohon balls.

•  Example signal of close to delivery: suddenly buying lots of scent-‐free soap, extra-‐big bags of cohon balls, hand saniDzers and washcloths, it

•  Pole found about 25 products, when analyzed together, allowed him to assign each shopper a “pregnancy predicDon” score.

•  Take a ficDonal Target shopper named Jenny Ward, 23, Atlanta: –  In March bought cocoa-‐buher loDon, a purse large enough to double

as a diaper bag, zinc and magnesium supplements and a bright blue rug.

–  There’s, say, an 87 percent chance that she’s pregnant and that her delivery date is someDme in late August.

Target staDsDcian Andrew Pole


Target Case as a Data Driven Business Model

•  Value: Know customers life change events.

•  Key Algorithm: Scoring and regression

•  Decision/process:

targeted coupons at the right Dme.

•  Goal: Increase wallet

share from exisDng customers

Data Model/Source

Internally Collected

Externally Collected

Purchased

Structured

Unstructured

Streamed

4/28/14

5


Target as a Measurement Process: ConDnuous Learning Model

1

2

3

4

6

5

Current state, model, system

What decision do you want to affect, what business case for measurement, (know why to avoid bias)

Hypothesis formulaDon, EsDmaDon, SimulaDon.

Filter by value of informaDon and risk orientaDon (another bias)

Data collecDon, samples, Bayes’, correlaDons, machine learning, etc

Interpret, decide implement (will affect current state

Does not need to take a long Dme. It’s a process, not a one Dme measure


1

2

3

4

6

5

Current state, model, system

What decision do you want to affect, what business case for measurement, (know why to avoid bias)

Hypothesis formulaDon, EsDmaDon, SimulaDon.

Filter by value of informaDon and risk orientaDon (another bias)

Data collecDon, samples, Bayes’, correlaDons, machine learning, etc

Interpret, decide implement (will affect current state

Current State: Guest ID + Shopper Info

Decision: targeted coupons during

pregnancy

Business case: life change events

EsDmaDon based on baby registry

Hypothesis: product

signals

Value of Perfect InformaDon, reward biased

CorrelaDon tesDng.

Assign

Pregnancy Score

Set new coupon strategy, observe

results

Business Model

Target as a Measurement Process: ConDnuous Learning Model

4/28/14

6


Top 8 Business Models Using Data 1.  Knowing your customer, leading to beher targeDng

and relaDonship. E.g. Target, Disney, Nenlix

2.  InformaDon based beher services. E.g. UPS, FedEx

3.  Data driven reliability. E.g. GE, BMW, Siemens

4.  InformaDon Brokers, Arbitrage, and Trading OpportuniDes: Investment funds.

5.  Improving the customer journey/experience.. E.g. Harrah’s

6.  Risk Management, regulaDon, and compliance

7.  Efficiency or Beher Performance per dollar cost. General IT, SAP, etc

8.  FuncDonal ApplicaDons: HR/Hiring, OperaDons etc.. Eg Walmart


Any ApplicaDon: Data Driven Model

•  Value:?

•  Key Algorithm: ? •  Decision/process: ? •  Goal: ?

Data Model/Source

Internally Collected

Externally Collected

Purchased

Structured

? ? ?

Unstructured

? ? ?

Streamed ? ? ?

4/28/14

7


Top Business Models for Using Data

1.  Knowing your customer, leading to beher targeDng and relaDonship. E.g. Target, Disney

2.  InformaDon based beher services. E.g. UPS, FedEx

3.  Data driven reliability. E.g. GE and Siemens

4.  InformaDon Brokers, Arbitrage, and Trading OpportuniDes: Investment funds.

5.  Improving the customer journey/experience.. E.g. Harrahs

6.  Risk Management, regulaDon, and compliance

7.  Efficiency or Beher Performance per dollar cost

8.  FuncDonal ApplicaDons: HR/Hiring, OpetaDons etc..

Usage Models •  Efficiency (save money) •  Wallet Share (top customers spend more Dme and money with you) •  Brand alignment (It reinforces how people think posiDvely about the company)

Value to Business Customers

More Value


A Common Cycle

14

Ideation for Data Driven Concepts!Induction, building, story-telling, verification, and adaptation

Develop: • Value ProposiDon • Business Model:

4/28/14

8


Inside vs Outside PerspecDve

Inside Firm PerspecDve (Data Intrapreneurship)

•  Start sample project •  Get execuDve sponsor •  Choose Metrics •  Include suppliers and partners •  Realize

Outside of Firm (Entrepreneurship)

•  What is the business model (ConsulDng, data as a service, investment fund, etc.)

•  Customer and validaDon of value proposiDon

•  Product/Service/CompeDDon •  PromoDon •  Branding


The Berkeley Method of Entrepreneurship

A holistic approach to entrepreneurship education

4/28/14

9


Level 1: Strategies, Tactics, and Judgment!Teaching effectiveness of strategy, tactics & execution! e.g. opportunity recognition, pivots, MVP, raising funds, tools, frameworks, …

Level 2: Mindset, Culture, and Social Psychology!Psychology of being an entrepreneur! e.g. trusting, risk assessment, communication, overcoming social barriers, rejection therapy, fail training…

Level 3: Infrastructure and Supporting Environment!Safe and effective environment ! e.g. diverse networks, ability to connect, facilities, services, clarity of rules of engagement, and mentors…

The Berkeley Method: A holistic approach to entrepreneurship content


1.  Agree that you will get help from others, and pay it forward.

2.  Friend or Foe: If you can’t tell: Learn to trust others without expecDng anything in return.

3.  Realize a something new by inducDon, and then learn to communicate the story with a new language.

4.  Entrepreneurs believe they can change the world.

5.  Make deals that seek fairness (in posiDve sum transacDons), not advantage (in zero sum transacDons).

6.  Its necessary to be Wrong someDmes. Plan to Experiment. Plan to Fail. (Fail Fast) Analyze, Adapt and repeat. The smarter you think you are, the harder this is going to be.

7.  Diversify your networks. Connect to people you would not normally, then go and listen. Open Up. And connect them to others.

8.  Be a role model for other entrepreneurs and innovators.

If everyone in your community acts like this, you will have a vibrant entrepreneurial culture.

Cultural Behaviors for Entrepreneurs

4/28/14

10


Raw Polished

The CET Curriculum Journey

Successful Alumni and New Ventures

Venture Lab

Sky-‐Deck

Challenge Labs

Product Management

Tech Leadership

Global Ventures

Tech Entrepreneurship A Richard New

ton Lecture Series

Ecosystem Development and Virtual CET!Powerful Networks: students, mentors, entrepreneurs, customers, and investors

CET Courses ExperienDal Learning / Venture AcceleraDon


CreaDng an InnovaDve Culture

Induc've Learning

Diversity = Value

Learn While Doing + Cases Studies

Games + Exercises

Industry and Social Challenges

Tes'ng with Real World Goals

Cultural Rules for Entrepreneurs Students

interact directly with problems

4/28/14

11


Contact: Ikhlaq Sidhu Chief ScienDst & Founding Director, Center for Entrepreneurship & Technology Faculty Director, Engineering Leadership Professional Program (ELPP) IEOR Emerging Area Professor, UC Berkeley [email protected] cet.berkeley.edu

Data Driven Business Models-GE - · PDF file4/28/14 1 Ikhlaq&Sidhu,&contentauthor& Ikhlaq...

Documents

Transcript of Data Driven Business Models-GE - · PDF file4/28/14 1 Ikhlaq&Sidhu,&contentauthor& Ikhlaq...