The CDO Agenda: Competing with Data - Strategy and Organization

Competing with Data:

Strategy and Organization

Thomas C. Redman, Ph.D.

“the Data Doc,”

Navesink Consulting Group

www.navesinkconsultinggroup.com

Dataversity Webinar, March 2014

/Redman-Competing-March2014 T.C. Redman, Page 1© Navesink Consulting Group LLC, 2000-2014

Data at Grandma’s

We find some real nuggets—that

lead to fundamental innovations

and create new industries. Good things follow:

• The economy grows

• Health care is better

and less costly.

• We’re freer and

safer.

/Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 2

FOUNDATION: The data are high-quality—

we know we can trust them.

People, top-to-bottom,

bring more data to the

decision-making table

We use them to

Improve product

and service

Junior Executive


VS

Family Practitioner


VS

Rising Middle Manager


VS

CEO Capital Request


Our future…

I better get

involved!

More tech

b#@S%!VS

“Data come up in every single

conversation”

POINT COUNTERPOINT

Individually, nothing more

than tough social and

organizational issues.

Collectively, something

deeper.

The successful have always

sought and taken advantage

of superior data.

Data, especially big data,

are exploding everywhere.

Impressive “big data”

successes, from all over.

Viewed through the “data

lens,” the financial crisis is a

colossal failure of data.


Opinion:

A full-strength data revolution is brewing!

It is not “big data,” it is all data.

Revolutions are chaotic, messy and inherently

unpredictable.

No one will remain untouched.

There are no roadmaps. By the time they

appear it will be too late.

The technological challenges are tall. These

pale in comparison to the organizational

challenges.


The Four Most Common Things I Hear

“We’re data rich and information poor.” (e.g., “We’ve not

thought through how we’ll compete with data

“I’ve been in this industry twenty-five years. Trust me.

These data are as good as they can possibly be.”

“Tom, you’ve got to keep in mind that we are much

more siloed than the other companies (industries, etc)

you work with.”

“If its in the computer, it must be IT’s responsibility.”


Today’s organizations are unfit for data

Don’t know how to compete with data, nor gained

enough experience to do so in a sensible fashion.

Lack talent, up and down the organization chart.

Silos impede data sharing.

Quality is essentially unmanaged.

Responsibility for data buried in the bowels of IT. Step

one: Move it out!

WORKING THROUGH THESE ISSUES IS THE

MANAGEMENT CHALLENGE OF OUR

GENERATION


Bottom Line

The leadership challenge in a nutshell:

A full-strength data revolution is brewing

Today’s organizations are stunningly unfit for data

So… what to do?

Sort out how to compete with data

Build organizational capability:

Get responsibility for data out of IT

Quality is pre-requisite (and we know what to do!)

Think end-to-end.

Develop and exploit data that are uniquely your own.

Recognize this will take a lot of people spread throughout


So far, I’ve identified eighteen distinct

ways to “put data to work”Provide (Sell) Content

New Content

Re-package

Informationalization

Unbundling

Exploiting Asymmetries

Closing Asymmetries

Facilitators

Own the Identifiers

Infomediation

Big Data/Advanced Analytics

Privacy and security

Training

New Marketplaces

Infrastructure technologies

Information appliances

Tools

*Working out “what’s right for us”

is the key challenge for senior

leadership!

*Every organization must think

through the four in bold

• Internally

Improve operational efficiency

360°-view

Data-Driven Culture

/Redman-Competing-March2014 T. C. Redman, Page 12© Navesink Consulting Group LLC, 2000-2014

Four Basic Strategies

Innovation (Big Data/Advanced Analytics):

Find hidden nuggets in the data and,…

Content: Provide or exploit content that others

don’t have.

Build a Data-Driven Culture: Make better

decisions, bottom-to-top and across the

company.

Be the low-cost provider: Superior data

quality keeps costs down!


I’m Excited AboutInformationalization

Eisner: “Content is king”

Basic idea: Make existing products and services

more valuable by building in more data and

information

Ubiquity: e.g., The hospital gown.

Available to all: Doesn’t require massive

quantities of data, people with advanced degrees,

or capital investment.

Caution: Customers already in information

overload./Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 14

High Quality Data is Pre-requisite

Poor quality the norm.

Enormous, mostly hidden, costs.

Decision-makers discount data they don’t trust.

And analyses based on them. Wisely so.

In advanced analytics, data are highly

leveraged. Recall the the financial crisis.


For Data, Only Two Moments Really Matter


The moment of useThe moment of

creation

The whole point of

data quality

management is to

connect the two!

Note that they do

not occur in IT

Data Quality Done Properly


Each error not made saves an average of $500.

This amounts to millions quickly!

0.5

0.6

0.7

0.8

0.9

1

0 5 10 15 20Fra

cti

on

Pe

rfe

ct

Re

co

rds

Month

First-time, on-time results

Accuracy Rate mean control limits target

It is so easy for accountability to shift

downstream!!!


Here’s how

you do

number 3!

Where does analytics fit?

Basic

Process

Improvement

New,

sophisticated

algorithms

Series of

Fundamental

Discoveries

In the line:

Everyone

involved

Permanent

“lab”

Analytical “sophistication”

“Home” for Analytics

/Redman-IDQ-Nov2013 T. C. Redman, Page 19© Navesink Consulting Group LLC, 2000-2013

Project team

wo/line responsibilities

“One-time”

opportunity

Really close

to, but not in

the line

Think End-to-End

Whatever strategy you select, you need a D4-Process:

Data: High-quality, well-understood, potentially-

interesting data is pre-requisite.

Discovery: Finding something truly interesting in the

data

Delivery: Getting the results to a decision-maker, into

an ongoing process, into a new product/service,

etc.

Dollars: Making money from the data, discovery and

delivery

Expect none to be easy!

/Redman-Competing-March2014 T. C. Redman, Page 20© Navesink Consulting Group LLC, 2000-2014

© Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 21

It helps to have something others don’t!

Your data are uniquely your own.

And you make more each day.

Subtle and nuanced.

Some, maybe most data become standardized to facilitate communications.

A small fraction offer opportunity for sustained advantage.

These data merit special attention!

/Redman-Competing-March2014

Putting data to work requires new skills and

talent, up the organization chart

Everyone/Culture: So far, Information Technology has not

delivered on its promise to make everyone smarter.

Analysts: The truly great ones are in short supply.

Managers:

For every good+ analyst, need dozens of good+ managers.

In every “clever analysis” that actually bears fruit, the “unsung

hero” is a manager who took a chance!

Executive Leadership:

Stone-cold, sober evaluation of “what we can actually pull off.”

Sooner or later, all change is top-down.

/Redman-IDQ-Nov2013 T. C. Redman, Page 22© Navesink Consulting Group LLC, 2000-2013

Federated Structure for Managing Data

People Management Data Assets

Regular people and

managers: Day-in, day-out

people management.

Regular people and

managers: Create high-quality

data. Put data to use in novel

ways.

Departmental HR: Help their

units find and advance the

talent they need

Departmental DG: Facilitate

DQ, analytics, delivery, day-in,

day-out innovation.

Corporate HR: Succession

planning, pay scales, etc

Corporate DG: “metadata, ”

unique data

Data Lab: innovation via big

data, advanced analytics


I hope I’ve excited, and scared, you!

The leadership challenge in a nutshell:

A full-strength data revolution is brewing

Today’s organizations are stunningly unfit for data

For most, it is too soon to set strategy. But it is time to get

moving

Quality is pre-requisite. Move responsibility out of IT!

Experiment with ways of competing with data

Think end-to-end

Sort out which data are strategic.

Build organizational capability.

And above all BE COURAGEOUS!


© Navesink Consulting Group LLC, 2000-2014 T. C. Redman, Page 25

Questions?

Thomas C. Redman, Ph.D.

“the Data Doc”

+1 732-933-4669

[email protected]

www.navesinkconsultinggroup.com

/Redman-Competing-March2014

/Redman-Competing-March2014 © Navesink Consulting Group LLC, 2000-2014 NCG, Page 26

Thomas C. Redman, “the Data Doc”

Ph.D., Statistics, Florida State, 1980.

Conceived and led the Data Quality Lab at AT&T Bell Labs.

Formed Navesink Consulting Group in 1996.

Helped dozens of companies think through, define, and advance their data and data quality programs.

Led development of most of today’s best-practice data quality management methods & techniques.

Latest and greatest: “Data’s Credibility Problem,” Harvard Business Review, December, 2013.

Data Driven: Profiting from Your Most Important Business Asset, Harvard Business School Press, 2008.

Known bias: “Data are quite obviously the key asset of the Information Age. Yet today’s organizations are singularly ill-designed for data. This leads me to conclude that learning to compete with and organizing for data is THE management challenge of the 21st century.”

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