The document discusses the accelerating rate of change in information technology and its effects on various sectors, emphasizing the evolution of the CIO's role from technical management to encompassing broader strategic, financial, and human dynamics. It highlights the importance of cloud computing as a transformative force and presents challenges and opportunities associated with managing information flow and organizational behavior in this context. The future of IT infrastructure reveals a shift towards hybrid systems, requiring adaptability and a focus on increased collaboration and decision-making efficiencies.

1. Logistics, Data in Motion and
Paradigm Shift of the CIO
The economics and psychology of the flow of
information
Vince Kellen
Chief Information Officer
University of Kentucky
vkellen@uky.edu
4/29/2012
1

2. Change
The only thing that seems stable is the
overused truism that change is permanent.
What is also not in dispute is that the rate of
change has accelerated and is continuing to
increase.
Information technology is the primary
accelerant in the recent increased rate of
change.
The effects of the increase in the rate of
change are being felt in all aspects of life:
personal, careers, social structures,
governments, climate.
The increase in the rate of change is without
precedent in human history. We are all
pioneers.
2

3. The [gradual, sudden] shift
 CIO Past
• Insourcing networks, data centers and software engineering
• Configuration management
• Stability, reliability
 CIO Current
• In/outsourcing networks, data centers, enterprise software
• Innovation
• Transformation
 CIO Future
• Cloud services
• Venture investor, organizational psychologist
• Information logistics expert
3

4. What is creating this dynamism?
The
computer!
4

5. What is creating this dynamism?
 Rising information intensity and flow
• Massive growth in density, quantity and diversity
• Dramatic improvements in breadth, ease and speed of access
• Global collaboration
 Faster innovation, mimicry
• Business process replication
• IT process replication (e.g., cloud, ITIL, enterprise architecture, PMO)
• Speed to market of new offerings
 IT is affecting industry competitiveness
• Lower barriers to entry, increased market turbulence, major competitors
changing positions
– From “Scale without mass: business process replication and industry dynamics.” E. Brynjolfsson, A. McAfee, M. Sorell, F. Zhu.
Harvard Business School Technology & Operations Mgt. Unit Research Paper No. 07-016 (2007).
• Individual and organizational human systems are responding to this pressure
5

6. What are the consequences of this change?
 Investments in IT capital are continuing
• Buoyed by dramatic price/performance gains (e.g., Moore’s Law)
 First mover advantage might not mean much
• New startups grow and die quickly or get eaten by bigger fish
• This results in increased consolidation in IT intensive industries
• But… remaining dominant players leapfrog each other
• And... Industry consolidation grows significantly
– Is higher education about to become IT intensive like service and manufacturing sectors?
 IT leaders will need more financial, strategic and human skills
• Continued growth in IT investments demands improvements in productivity
(reduced costs, more output)
• Market dynamics require nimble architecture that all can enjoy (no sustainable
competitive advantage)
• The impediments to superior use of tools (in this case IT) will lie more and
more in organizational and individual tailoring and adoption
6

7. Can this change
Probability of occurrence persist?
1
Zone of optimal
information advantage
(edge of chaos)
To gain an edge,
To avoid losing,
agents will develop
agents will develop
more complex
simpler models,
models, with longer
with shorter time
time horizons,
horizons resulting
resulting in
in decreasing
increasing
dynamic complexity
dynamic complexity
0
Level of Complexity
0 1
Order Chaos 7

8. The consequences for failing to catch up
 Abundance of information Destabilizing
without improvements in human gap
absorption and decision making 1970?
will result in a growing gap in the
breadth and quality of
information actually used by
people and organizations
 This gap (a form of information
ambiguity) could increase
overall instability and
uncertainty. Agents operate out
of distinct world-views that filter
information
 This gap makes available
competitive opportunity for those
who can understand more,
provided some balance between
order and chaos remains 8

9. What can slow down dynamism?
 Human attention
• Our ability to process information limited to waking hours
• We will need more automated decision making, reserving
human attention for strategic maneuvers and change
 Culture
• Cultures and their attendant legal systems are slower to
adjust to automated decision making and new concepts
 Personal and organizational defensiveness
• While change brings opportunities, it threatens people
• These changes will not be without a battle of sorts
9

10. Speaking of change, now let’s talk about the
cloud…
First some IT facts of life
10

11. Server
Server
Hugger
Server
Hugger
Trainee
11

12. What is this about cloud?
 The new outsourcing
• Cloud represents a new way of integrating technologies (and business
processes) so that the institution relies on external vendors for basic
services
• Cloud is very real, very big and will transform IT
• Morgan Stanley May 2011 analysis expects adoption to be about 51%
of organizations and about 22% of the IT workloads run in the cloud in
three years. On premise growth in servers is expected to be flat or
shrink
• All major vendors are committing >$1 billion each in cloud technology
 What makes cloud computing unique?
• Widely used, well understood and generic components
• Quick provisioning and de-provisioning
• Flexible contracting and procurement
12

13. Cloud vernacular
 Software as a service (SaaS)
• Software hosted elsewhere. Higher education has been steadily adopting SaaS
• Examples: Hobson’s CRM, Digital Measures, ServiceNow IT support
 Infrastructure as a service (IaaS)
• Infrastructure hosted elsewhere. Higher education has NOT yet adopted this
technology. General purpose server computing can be hosted with a vendor or
consortium
• Amazon’s elastic computing and storage solutions are examples of ‘generic’ cloud
• Large vendors are bringing custom, enterprise cloud solutions forward now
 Platform as a service (PaaS)
• This includes tools to create applications in the cloud
• Examples include Microsoft Azure, Force.com
 High performance computing (HPC) as a service may be coming
• National labs have long since been an ‘outsourced’ provider of HPC
• Expect more HPC university consortiums, offerings be large vendors
• Cost of electricity, generic workloads make HPC as a service attractive
13

14. So, what does this mean for data centers?
First, let’s look at an institution’s data center of the present…
14

15. 15

16. Now let’s look at an institution’s data center of the future…
16

17. 17

18. What does this future look like to our server hugger?
18

19. 19

20. 20

21. Sizing capacity
Instead of sizing on-premise computing at 100% of potential usage, size at some
amount lower and ‘burst’ out to cloud providers for ‘overflow.’ This can save costs
100%
??
Utilization
0%
Jan Apr July Oct Dec
21

22. Types of workloads
 Virtual desktops for student access to academic software
• Peak usage in midterm and final weeks
• Low usage during breaks
 ERP processes
• Peak usage during enrollment periods
• Testing and development of new ERP functionality
 Storage
• Take very large amounts of data, infrequently accessed to large-scale,
low-cost providers
 Disaster recovery
• Instead of maintaining a hot/warm site, secure contracts for quickly
expanded processing
22

23. All forms of cloud will be useful
 Software as a service will continue to be important
• Enforce real-time data integration for quick user account provisioning and
same-day data analysis
• Review contracts for legal gotchas and security holes
 Infrastructure and platform as a service will become the center of attention
• Select multiple vendors to encourage both diversity of supply and competition
• Match workload characteristics to vendor strengths
 Key challenges for the immediate future
• Strong ‘cloud orchestration’ tools to help IT manage on/off premise computing
with multiple vendors
• Easily managed, real-time data integration across multiple cloud providers
• Flexible contracting and pricing models, especially in the area of software
licensing
23

24. Examples
 In use today @ UK
• Google and Microsoft email (SaaS)
• Digital Measures (SaaS)
• Hobsons CRM (SaaS)
• Xytracs – Accreditation software (SaaS)
 Testing today @ UK
• IaaS for ERP
• IaaS for HPC
 In use tomorrow?
• Business intelligence and analytics in the cloud?
• Learning management systems in the cloud?
• Supercomputing in the cloud?
• Desktops in the cloud?
• e-Textbooks in the cloud?
24

25. Will everything be in the cloud?
 Not for the foreseeable future (4-8 years)
• Costs. We can save costs by running dedicated workloads locally (this
may change!)
• Risk. We need some ability to be immune to vendor supply chain
disruption (other industries get by without any local production!) or the
cloud market is emerging and still not mature
• Cost of data computing versus cost of data transmission. Some
workloads will just be cheaper to process locally than transmit the data
across a network (think very large files, super rich medical imaging)
• Some software isn’t technically capable of running in the cloud (True!)
• Some software vendors can’t figure out how to price their software in
the cloud (True!)
 For all these reasons, a hybrid cloud strategy is important
25

26. Current model: Slow, big central data center
SaaS
External
Solution A Data
Center A
Firewall
Data SaaS
Solution B
Center
External
Data
Center B
SaaS
Solution B
26

27. New model: Fast, small central data center
SaaS
External IaaS Vendor B Solution A
Data
Center A
External
Data Data
IaaS Vendor A Center Center B
Integration orchestration and security layer
SaaS SaaS
Solution B PaaS Vendor A Solution C
27

28. Moving from ‘anticipate slowly’ to ‘react quickly’
 Since the beginning, IT has planned capacity in either 30 year
chunks or 5-10 year chunks
• 30 years for the design and use of a data center
• 5-10 years for the selection and use of servers and storage
• Moore’s Law and incremental capacity increases provide the rest
 In a ‘pull’ approach, IT services are provisioned much more quickly.
Using self-service cloud approaches both on- and off-premise this
can be in minutes
• No lead time in provisioning, no ‘shelf time’ as equipment sits in
storage rooms, automated provisioning
– Virtual servers, operating systems, application installation, database loading,
network provisioning, security policies
 If the entire system moves faster with far fewer manual steps, what
happens?
28

29. What business benefit does ‘Pull’ really create?
 Organizations can turn a new idea or change into action much quicker
• This can allow for faster delivery and it can allow for faster failing!
• Can organizational decision making keep up?
• To borrow from True Lean, eliminating waste (time) can save
effort/cost, leading to best-in-class efficiency
 IT shifts its focus from mundane provisioning and support activities to:
• Assisting in the design of ideas
• Managing suppliers
• Optimizing IT costs
• Review of the effectiveness of ideas implemented
 Does this mean IT staff will no longer be needed?
• No!
• We have more demand for new work than we can keep up with. We can shift
people to new roles that are needed to contribute to new work
29

30. What should this mean for university operations?
 IT should be directed to:
• Measurably, over time, lower the cost of IT relative to revenue
• Enable improved outcomes for both learning and research
• Accelerate the development of business insight for both cost savings & growth
 IT should be a scalable infrastructure to help the institution find reallocations and new
revenue while maintaining quality
Revenue $
Direct labor $
Administrative processes and
IT/process infrastructure $
Year 0 Year 1 Year 2 Year 3 Year 4 …
30

31. (Pause)
How can we harness the forces of faster information flow and
increased rate of change without losing our minds?

32. Let’s review the CIO role in this…
 What do we have so far?
• Dynamism (internally and externally) is growing
• Business process (and those within higher ed) are replicating quickly
• IT processes are replicating within the vendor community and between
organizations
• The impediments to successful use are likely to be increasingly
human, not technical
• The investments in this whole ball of wax continues to grow, possibly
requiring more complex financial acumen to manage
 The role of the CIO is shifting
• Away from mainly technical infrastructure configuration management
• To the dynamics of information costs (technical) and uses (human)
32

33. The role of organizational capital
Investments in computers + people
are synergistic
Organizational capital:
• Degree of self-managed teams
• Employee involvement in groups
• Diversity of job responsibilities
• Who determines pace of work
• Who determines method of work
• Degree of team building
• Workers promoted for teamwork
• Off-the-job training
• Degree of screening new employees
for education
From “Intangible Assets: Computers and Organizational Capital,”
E. Brynjolfsson, L. Hitt, S. Yang. Center for eBusiness @ MIT,
MIT Sloan School of Management. Paper 138. (2002).
33

34. A lot stands between bits and appropriate action
 The purpose of IT is to
improve agent action
Action
(individuals & organizations)
• Both efficiency and
appropriateness of action
Organizational defensiveness
 When millions are invested
Peopleware
and the payoff [is, is not] not
Governance, teamwork
achieved, who should take
[credit, responsibility]?
Individual motivation
• Can the CIO credibly say
Hard/software
“They made me do it?”
Visualization, usability
Infrastructure, ERP
34

35. Information immunity
 “You don’t understand. On the 22nd floor, we work in a fact-free
environment.”
 While computing excels in turning data into information, getting
information shared with fidelity across human beings is difficult
• Different disciplines create different mental models. Information
mutates or is rejected, depending on the mental models one has
• Double-loop learning is not so common
• Individual information processing orientation matters
– Are you predominantly a Data->theory or theory->data person?
• Power relationships, threats to position, conflict, group-think can filter
out information
 Is this why investments in organizational capital are synergistic with
investments in IT?
35

36. Boyd’s OODA “Loop” Sketch
Observe Orient Decide Act
Implicit Implicit
Guidance Guidance
Unfolding
& Control Cultural & Control
Circumstances Traditions
Genetic
Heritage Analyses &
Feed
Observations Forward
Synthesis Feed Decision Feed Action
Forward Forward
(Hypothesis) (Test)
New
Information Previous
Outside Experience Unfolding
Information Interaction
With
Unfolding Environment
Interaction Feedback
With
Environment
Feedback
Note how orientation shapes observation, shapes decision, shapes action, and in turn is shaped by the feedback and other
phenomena coming into our sensing or observing window.
Also note how the entire “loop” (not just orientation) is an ongoing many-sided implicit cross-referencing process of
projection, empathy, correlation, and rejection.
From “The Essence of Winning and Losing,” John R. Boyd, January 1996.
http://en.wikipedia.org/wiki/OODA_loop, http://danford.net/boyd/

37. CIO Past Human
Market
Stable Dynamic
Scope
Technical
Focus of work
37

38. CIO Present Human
Market
Stable Dynamic
Scope
Technical
Focus of work
38

39. CIO Future? Human
Market
Stable Dynamic
Scope
Technical
Focus of work
39

40. A future state – financing and contracting
 Computing supply chain management
• Standard, spot, futures, options contracts
• Options exchange
• Use of brokerage and risk management services
• National and international network architecture
• Monitoring, measuring, pricing the flow of information between systems
• The institution can be both a buyer and seller
• Not all architectures will be equal, some snake-oil will be sold
 The physical logistics of information will become more complex as
price/performance optimization options grow
• The network will be the critical scarce resource. It is physically and legally
constrained in ways all the other layers of IT are not
• Data center automation
– Scheduler, rule-based, statistical inference/correlation engine
• Cost of compute, transport, storage and policy must be determined
• Costs + workflow type (CPU, I/O, disk, priority, time-to-market) must be optimally
matched to provider 40

41. A future state – from push to pull
 Orchestration of pull business architectures
• How do you get business processes and technology to be
created/altered quickly?
• How do to streamline business processes across the board?
• How do you effectively and efficiently tailor valuable, core processes?
– Research, teaching, community service, healthcare
 Design of a dynamic hybrid infrastructure
• How do you ensure your network will take your data to where it needs
to go?
• How do you manage security in this more complex network
environment?
• How do you know when/where to process workloads?
– (Compute costs + network costs + policy costs) must be [dynamically, statically]
compared with provider capabilities
41

42. A future state – organizational development
 “Peopleware”
• Once you have a dynamic, cost-effective, economically tractable IT
infrastructure, you have to have an organization capable of using it
– The Tale of the New Lamboughini
• How does the CIO get “footing” to encourage a more rigorous discussion of
larger organizational issues?
– To the degree that IT is both competitive and costly! Not all organizations will
require this full-throated conversation (yet)
• The logistics of the psychological flow of information will emerge as
the next competitive advantage
– We will need to develop teams that are expert at teamwork, non-defensive
management interactions and team chemistry
– We will need to invest in the right blend of organizational capital elements
 Outcomes
• How much operating budget can this save relative to competitors? 2x?
• How much opportunity can it create relative to competitors? 5x?
42

43. Summary
 Computation and transport will continue to dance with each other
• 20 years from now, computing systems performance will matter!
• Denser imaging will require high performance computing data reduction and faster
networking
• Network closets will be come HPC closets adjacent to equipment quickly throwing off
vast amounts of data
• Computation and transport will merge and differentiate in many ways to deal with
performance issues
– E.g., disk architectures today are benefitting from ‘in-flight’ computation, desktop virtualization is exploiting local
CPUs and graphics processors (wherever they are) to save on network latency and compute resources
 The individual and organizational dysfunctions are enduring
• The knitting together of human/technical systems is the stuff of competitive advantage
• The role of the CIO is likely to be strengthened and heightened as IT-induced
competitiveness continues
• The role is shifting to mastery of some abstract financial concepts and more difficult
human dysfunctions, dynamics and teamwork skills
43

44. Final thoughts
As information flows from a complex supply chain to a complex
internal value-network, between systems and human brains,
and with many technical and psychological impediments and
accelerants, someone has to plan, monitor and nudge forward
this strategic investment
Why not the CIO?
44

45. “If you aren’t confused, you haven’t been paying attention!”
– Tom Peters
QUESTIONS?
45