Today's social media and cloud computing in business environment

MANAGEMENT INFORMATION SYSTEMS 2014 – JARI JUSSILA @JJUSSILA
TODAY’S SOCIAL MEDIA AND CLOUD
COMPUTING IN BUSINESS
ENVIRONMENT

OUTLINE
• Personal experience on information systems
• Theory and models on how to develop and acquire social media and
cloud computing applications from systems perspective
• How social media and cloud computing applications are changing
management information systems in today’s business environment
NOVI RESEARCH CENTER
TUT.FI/NOVI
TWITTER: @NOVIRESEARCH
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INFORMATION SYSTEMS BACKGROUND
• 1996 Technical documentation specialist, Healy Chemicals Ltd. (UK)
• 1997 Data base programmer and administrator, Healy Chemicals Ltd. (UK)
• 1998 Computer sales and support, Puhetta Ltd.
• 1998 System administrator, Kuljetusliike K. Vierikko Ltd. & Kuljetus Veli Nikkilä Ltd.
• 2001 Trainee / technical documentation, Säteri Ltd.
• 2003- Entrepreneur / IS consultant, Ins. tst. Jari Jussila
• 2002- Project engineer, HAMK University of Applied Sciences,
2004 e.g. PLC, SCADA, MMS, ERP, BI
• 2007- Researcher, Tampere University of Technology
2009 e.g. Web 2.0, Scrum, Agile and Lean software development
• 2009 CEO / IS & KM & M consultant, Yoso Services Ltd.
2011 e.g. Cloud computing (SaaS and IaaS)
• 2009 Project planner, Technology Centre Innopark
e.g. Social media
• 2010- Project manager, Tampere University of Technology
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WHAT IS A MANAGEMENT INFORMATION
SYSTEM?
Goal: to inspire double loop learning
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SINGLE-LOOP AND DOUBLE-LOOP
LEARNING
Governing
variables
Action strategies
Results /
consequences
SINGLE-LOOP LEARNING
DOUBLE-LOOP LEARNING
Assumptions / beliefs
Ref. Argyris & Schön 1978; Argyris 1990
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HOW TO DEVELOP OR ACQUIRE (I.E. MAKE OR BUY)
INFORMATION SYSTEMS IN TODAY’S BUSINESS ENVIRONMENT
Ref. Lyytinen 1987
e.g. Waterfall e.g. Agile
e.g. Lean Startup
e.g. Vanguard
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WORK SYSTEM THEORY AND WORK
SYSTEM METHOD
Ref. Alter 2013
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ACTIVITY THEORY, ACTIVITY SYSTEMS
AND EXPANSIVE LEARNING
Ref. Engeström 2001; Engeström 1987
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INTERACTING ACTIVITY SYSTEMS – EXPANSIVE
LEARNING IN INTERACTING ACTIVITY SYSTEMS
Instruments
Rules
Division of
labour
Subject
Community
Transformation
Object ->
Outcome
Motivation
Division of
labour
Subject
Instruments
Community Rules
e.g. IaaS provider e.g. customer
Ref. Vartiainen, Aramo-Immonen, Jussila et al. 2011
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ACTIVITY SYSTEM –CYCLE OF
EXPANSIVE LEARNING
1. Questioning
2. Historical analysis & actual-empirical
analysis
3. Modeling the new solution
4. New model
5. Implementing the new model
6. Reflecting on the process
7. Consolidating the new practice
WORK SYSTEM LIFE CYCLE
1. Initiation
2. Development
3. Implementation
4. Operation and maintenance
Ref. Vartiainen, Aramo-Immonen, Jussila et al. 2011
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COMMAND & CONTROL VS SYSTEMS THINKING VIEW
Command and Control Thinking Systems Thinking
Top-down, hierarchy Perspective Outside-in, system
Functional Design Demand, value and flow
Separated from work Decision-making Integrated with work
Output, targets, standards: related to
budget
Measurement
Capability, variation: related to
purpose
Contractual Attitude to customers What matters?
Contractual Attitude to suppliers Cooperative
Manage people and budgets Role of management Act on the system
Control Ethos Learning
Reactive, projects Change Adaptive, integral
Extrinsic Motivation Intrinsic
Ref. Seddon 2011
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LITERATURE ON HOW TO CHANGE MANAGEMENT THINKING IN
TODAY’S BUSINESS ENVIRONMENT
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EXAMPLES OF SOCIAL MEDIA AND
CLOUD COMPUTING ENVIRONMENTS
Public social media and cloud
applications
Business oriented public social
media and cloud applications
Private business oriented social
media and cloud applications
e.g. Google Documents e.g. Yammer e.g. phpBB
e.g. WordPress e.g. ZenDesk e.g. Confluence
e.g. Facebook e.g. SharePoint Online e.g. SharePoint Server
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Ref. Schubert & Jeffery 2012
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PRIMARY CHARACTERISTICS OF CLOUD
SYSTEMS
• Utility computing
• allow easy outsourcing of IT resources infrastructure, by moving the in-house
applications to a dedicated (public) CLOUD provider
• Elasticity
• allow the environment to – ideally automatically – assign a dynamic number of
resources to a task
• Availability and Reliability
• CLOUD systems build up on the internet of service principle to expose the services
in a highly accessible fashion, i.e. with minimal configuration and device
requirements (generally through a browser). CLOUDs enhance this aspect further
by virtualising the service / resource access, basically allowing access “anywhere,
anytime”
• Ease of use
• The fact is that CLOUDs can reduce the overhead for managing and administering
resources through automation and outsourcing, and should reduce the overhead
for creating highly available and reliable services
Ref. Schubert & Jeffery 2012
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SOCIAL MEDIA GENRES
Ref. Lietsala & Sirkkunen
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More on social media
tools and processes:
• Lietsala & Sirkkunen
Ref. Lietsala & Sirkkunen 2008
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ADOPTION OF CORPORATE
TECHNOLOGIES
Automating transactions Enabling collaboration and participation
Adoption of ERP, CRM, SCM
- Users assigned by
management
- Users must comply with
rules
- Often complex technology
investment
Adoption of Web 2.0 tools
- User groups can form
unexpectedly
- Users engage in high
degree participation
- Technology investment
often lightweight overlay to
existing infrastructure
Traditional IT
Web 2.0 tools
Time
1990s 2009
Productivity
Ref. McKinsey 2009
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Ref. Pirttilä 2014
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Changed service systems enabled by corporate technologies
Ref. Pirttilä 2014
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A DATA PERSPECTIVE ON INFORMATION SYSTEMS
WEB
BIG DATA
Web logs
Offer history A / B testing
ERP
CRM
ostotiedot
maksutiedot
segmentointi
tarjoustiedot
asiakaskohtaamiset
tukikontaktit
Sentiment
Dynamic Pricing
Affiliate Networks
Search marketing
Behavioral targeting
Dynamic Funnels
Social Network
External Demographics
Business Data Feeds
Pictures & Video
Speech to Text
Sensor Data
Product/Service Logs
SMS/MMS
User Generated Content
Mobile Web
User Click Stream
Location Data
Ref. Yli-Pietilä & Backman 2013; Valli & Ahlgren 2013
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EXAMPLE OF PREDICTION MARKETS
Ref. Wolfers & Zitzewitz 2004
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EXAMPLE OF NEW APPLICATION IN
SALES FUNCTION
• Concern over the taste of a new coffee
• Social media was followed
• Taste was fine, but price was too high
• Price was reduced the same day
Ref. Kaisler et al. 2013 Introduction to Big Data
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EXAMPLE OF NEW APPLICATION IN
SERVICE FUNCTION
• Business challenge
• Needed to gain deeper insights into the causes and combinations of
circumstances which led to warranty issues
• Needed to increase customer satisfaction through increased product quality
and reduced warranty issues
• Solution implemented
• Implemented a data mining capability to gain actionable insights across a
wide range of warranty issues
• Feedback of issue findings into product design process for improvements
and modified service patterns where these were demonstrated to have
contributed to warranty issues
• Demonstrated business value
• Reduced warranty cases from 1.1 to 0.85 per vehicle
• 5% reduction in warranty cases
• Annual savings of €30m approximately
Ref. IBM 2013 Improving Operational and Financial Results through Predictive Maintenance
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BIG DATA DRIVEN AGENT-BASED MODEL IN
PREDICTION BUSINESS DECISIONS
The average cumulative sales of PS3 and Xbox 360 predicted by the model
against the real cumulative sales of the two consoles.
Ref. Huotari et al. 2014 Winter Simulation Conference*
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Huotari, Järvi, Kortelainen et al. 2014

From reporting to operational analytics OPERATIONAL INTELLIGENCE
REPORTING
WHAT
happened?
Batch reports
ANALYZING
WHY
did it happen?
Ad Hoc,
BI tools
PREDICTING
WHAT WILL
happen?
Predictive
models
OPERATIONALIZING
WHAT IS
happening now?
Link to
Operational
Systems
ACTIVATING
MAKE
it happen
Automatic
Linkages
STRATEGIC INTELLIGENCE
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Yli-Pietilä & Backman 2013

NEW TRENDS IN MANAGEMENT
INFORMATION SYSTEMS
• Using collective intelligence and wisdom of crowds in decision
making
• e.g. Prediction markets
• Using real-time or near real-time data in decision making
• e.g. Starbucks product price optimization
• e.g. Telefonica customer support
• Using increased computing power in predicting results / options in
management decision making
• Automated decision making
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Slideshare: http://www.slideshare.net/Noviresearch
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MORE CONTENT ON KNOWLEDGE
MANAGEMENT:
Twitter: @Noviresearch ja @tietojohtaminen
YouTube: http://youtube.com/noviresearch
NOVI research center’s website
https://www.tut.fi/novi/
TUT.FI/NOVI

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