“tools and technology: how we tracked productivity and...
TRANSCRIPT
© 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: [email protected] or [email protected]* 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 <[email protected]> Subject: Re: YOUR PROPOSAL Date: Sun, 17 Nov 2002 09:54:23 -0500 Cc: [email protected], Geoffrey Parker <[email protected]> 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) [email protected]
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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/