“tools and technology: how we tracked productivity and...

© 2007 MIT Center for Digital Business. All rights Reserved.Proprietary & Confidential

“Tools and Technology: How We Tracked Productivity and Where We’re Going” *

May 16, 2007

Marshall Van AlstyneResearcher Scholar, MIT Sloan SchoolProfessor, Boston UniversityT: 617-253-0768 E: marshall@mit.edu or mva@bu.edu* Joint work with Sinan Aral and Erik Brynjolfsson

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“In the physical sciences, when errors of measurement and other noise are found to be of the same order of magnitude as the phenomena under study, the response is not to try to squeeze more information out of the data by statistical means; it is instead to find techniques for observing the phenomena at a higher level of resolution. The corresponding strategy for economics is obvious: to secure new kinds of data at the micro level.”

—Herb Simon

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Microscope led to Germ Theory!

van Leeuwenhoek discovered cells in the 1670s when he invented high powered microscopes

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Areas of Inquiry

0%10%20%30%40%50%60%70%80%90%

100%

Firm X Firm Y Firm Z

Least Most Med.

Behaviors &Perceptions

Topology &Social Networks

InformationContent

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Tools & Technology

The view from the E-Mail Microscope

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Gaining access to live e-mail

To: Marshall Van Alstyne <mvanalst@umich.edu> Subject: Re: YOUR PROPOSAL Date: Sun, 17 Nov 2002 09:54:23 -0500 Cc: averhey@umich.edu, Geoffrey Parker <gparker@tulane.edu> X-Originating-IP: 68.41.189.43

Ok, i will look for all the pieces today then and try to get everything in Fastlane tonight.

Meeting is up to you. I have to go to DRDA first thing in the morning to hand them all the PAFs so they can process all the proposals. The meeting is to give you one last chance to view the entire proposal package before DRDA pushes the "Send" button. We could also try to do this virtually so neither of us has to travel to the other site.

As far as footers go, let's not worry about it as long as you are page numbering each section individually. I usually add more information to the footer but I don't have time to worry about this detail.

Ann

Stop words are dropped; then the raw text is root-stemmed (e.g. “are”->“is”, “pieces”->“piece”), counted, and hashed.

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AnnMessage-ID: 00000000C74E9F197619354B912FA038789E97DD070095FBFC9E5C710C45AD83BE1BA97654F300000025D7D7000095FBFC9E5C710C45AD83BE1BA97654F30000015D02090000 Date: 11/17/2002 09:54:23 PM From: ChiUserWWW2 To: ChiUserWWW34 CC: ChiUserWWW2 , ChiUserEEE137 Subject: 2234380046220310381 -4543232654336644202 3187911263930032313 -8725299062034745550 6646063218832296471 Content: -7488330257252326972<8>; 3461049762598860849<5>; -4469441121190040841<4>; 4122472038465781083<4>; -2485003116886841409<3>; 8003219831352894262<3>; 1698764591947117759<2>; 5894537654329429962<2>; -9076192449175488644<2>; 7750988586697557362<2>; 8871153132300476476<2>; - 7527789141644698404<2>; 8763687632651980147<1>; 3129683954660429336<1>; -6916544271211441138<1>; 6293576012604293570<1>; -320692498224125839<1>; 8934872354483414290<1>; -6836405471713717833<1>; - 5975878511407257679<1>; -3014223241434893634<1>; - 8934856908841293615<1>; -857818984403519253<1>; 1344343662225282497<1>; 965941123633882107<1>; -3147930629716878416<1>; 7137519577624117188<1>; 7523708256417630601<1>; -6946268052250097500<1>; Attachment Number: 0 Attachment list:

This is what we “see”

Reconstructing semantics is difficult. We do not read attachments but do record type & size information (e.g. 157kb .doc file)

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The Survey

52 Questions• personal characteristics• time-use• value of tasks• technology skills • technology use• information sources• work habits• information sharing• perceptions

≥ 86% response rate

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Levels of Feedback

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Email habits show work patterns

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Contacts differ by job type

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Intermittent

Stable Social Network

Growing InterestR&D Problem Solving

Efficient Ops

Opportunity

Temporal Social Network CentralitySource: TeCFlow

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Topic threads show variety, simultaneity & prestige

Pairwise new topic thread initiation (red)Pairwise topic continuation (blue)Non-pair communication (out arrows)Shows average response delays (#)

Multiparty topic thread activity (width)Multiparty topic duration (days)Topic starts & stops (date)

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An E-mail “Fingerprint”

Consultant - Sent vs. Received

-12000

-10000

-8000

-6000

-4000

-2000

0

2000

4000

6000

8000

c10

c12

c14

c16

c18 c2 c21

c23

c27

c29

c30 c6 c7 c71 c9

ExternalInternal

Sent

Received

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© Jeffrey Heer & Marti Hearst

Others’ Tools: E-Mail Analysis

Zoomable View of Inferred Social Network

Currently visualizing search results for the terms “California”(yellow), “FERC” (orange), or both (red).

Color-coded categorization of e-mail content

Navigable timeline view of e-mail traffic

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Topology

Comprehending the Social Networks

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Social Network Efficiencies1. Connect to hubs

• Central nodes who bridge structural holes are significantlymore effective.

2. Send short messages• Consultants have higher

billings (.56, p<.01) and are more central (see 1).

3. Communicate declarativeinformation

• Gets better reply rates.• Procedural tips shared laterally

not across hierarchy (or better FTF)

4. Career Ladder• Explore early vs. exploit late

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Social Network Efficiencies1. Connect to hubs

• Central nodes who bridge structural holes are significantlymore effective.

2. Send short messages• Consultants have higher

billings (.56, p<.01) and are more central (see 1).

3. Communicate declarativeinformation

• Gets better reply rates.• Procedural tips shared laterally

not across hierarchy (or better FTF)

4. Career Ladder• Explore early vs. exploit late

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Social Network Efficiencies1. Connect to hubs

• Central nodes who bridge structural holes are significantlymore effective.

2. Send short messages• Consultants have higher

billings (.56, p<.01) and are more central (see 1).

3. Communicate declarativeinformation

• Gets better reply rates.• Procedural tips shared laterally

not across hierarchy (or better FTF)

4. Career Ladder – Lifecycle • Invest in channels early vs. • Use channels later

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Survey Summaries

Incentives & Behaviors

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There are culture differences. One firm shares more. Most disagree than info never enters DB

Responses to Information Sharing Questions 1-4

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

Firm XFirm YFirm Z

Q1: Colleagues give me credit for info that I share.

Q3: I volunteer all relevant info to colleagues.

Q2: Colleagues willingly share their private search info with me.

Q4: A lot of my personal knowledge never reaches the corp. database.

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Incentive theory works

Weighting of Compensation Structure

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Firm X Firm Y Firm Z

Whole company performanceProject team(s) performanceIndividual performance

Least Most Med.

Narrower incentives mean narrower info sharing.

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Firm X automates more processes

Perceptions of IT Applications

-1.00-0.80-0.60-0.40-0.200.000.200.400.600.801.001.20

Firm XFirm YFirm Z

Q7 We use info sys to coordsched & project handoffs

Q14 My data requirements are routine

Q15 For routine info, the process of getting it is automated

Q41 We mine our data for correlations and new ideas

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There are structural differences in process flow

How many people do you communicate with in a typical day...

in the following modes?

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

Firm X Firm Y Firm Z

Num

ber o

f peo

ple

OtherE-mailFace-to-face

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Emails “pose threat to IQ”

Lack of discipline responding to email reduced productivity by the equivalent of 1 night’s sleep.

“…average IQ loss was measured at 10 points, more than double the four point mean fall found in studies of cannabis users.”

Similarly, in our study, time spent and volume processedbear little correlation with productivity…

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Do larger personal rolodexes make you more productive?

Dr. Erik BrynjolfssonMIT Center for Digital Business3 Cambridge Center NE20-336

Cambridge MA 02139(T) 617-253-7054 (F) 617-452-3231erikb@mit.edu

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Recruiters with larger personal rolodexes generate no more or less output

• Less information sharing• Less DB proficiency• Lower % of e-mail read• Less learning from others• Less perceived credit for ideas given to colleagues• More dissembling on the phone

Instead, a larger private rolodex is associated with:

* p < 0.10, ** p < 0.05, *** p < 0.01, Standard err in paren.

Revenue $ $ for Completed Searches

Completed Searches

Multitasking Duration Duration (controlling for

MT)

Rolodex Size (Q50)

-10.2

(60.3)

-22.9

(32.6)

0.000

(0.001)

0.000

(0.001)

-0.013

(0.021)

-0.013

(0.016)

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What’s Next?

Getting Involved

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New Sites & Natural ExperimentsTranslation Firm

• Natural Experiments:– Pre/post new database– Pre/post new biz processes

• Also tracking: – Room presence– Telecom phone calls – Minutes with files

Insurance Claims Processing• Natural Experiments:

– Pre/post new database– Pre/post new biz processes

Call center• Star Trek badges!• Physical location & FTF contacts• Voice patterns, Link frequency,

Conversation dominance

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New: Physical Position Privacy!

Hash Stream 1

Has

h S

tream

2

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Example BenefitsIn 1999 Harrah’s Casinos

hired MIT PhD Gary Loveman to use customer tracking data and mine it.

Natural Experiments:• Slot machine floor plans• Target market: lo rollers vs

tourists & hi rollers• “Same Day” cash• Promotions: $125 hotel

stay + 2 steak dinners + $30 chips vs. $60 chips

Stock Price: 12.31-24.37

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New Horizons

Experiments• Control groups• Intervention with pre & post measurement

Measurable Work• Inputs & Outputs• Sales Contracts, Law Briefs, Marketing

Campaigns, Consulting Projects, Patent Filings, Recruiting Successes, Medical Diagnoses, Insurance Claims, Software Products, Architectural Models, Banking IPOs, etc. etc...

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Information Economics Research

Products &Network Effects

CommunicationsMarkets (Anti-Spam)

Information &Productivity

Economics ofOpen Source

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Thank You!

To Learn More About This And Related Research, Please Visit:

http://web.mit.edu/marshall/www/

marshall@mit.edu