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IT and Soft Computing : Impressions, Implications and Applications
Dr S G Deshmukh
Director
ABV-Indian Institute of Information Technology & Management, Gwalior
National Students Convention 2011
ITM Universe Gwalior 11March 2011
Motivation
IT has become all pervading in almost every walk of life
Lot of debate on use/utility of IT
Soft Computing : As a powerful tool
IT aided by Soft Computing ?
Relevance of IT in Management of Business ?
2
Part 1
Information Technology : Impressions and Implications
Use of Information Technology (IT)
IT as an enabler and facilitator
IT as a tool
IT for streamlining processes
IT for bringing in transparency and objectivity
IT helps in automation !
Impression 1: Role of IT
IT acting as strategic weapon to gain differentiation and advantage.
Assumption: IT’s potency and ubiquity have increased, so too has its strategic value?
Examples: Indian Railways, CBSE , State Transport
Truly strategic resource : Its not ubiquity but scarcity of a resource which brings sustained competitive advantage.
Impression 2.. Availability of IT Ubiquity of resources transform them from
potentially strategic resources into commodity factors of production .
They are becoming costs of doing business that must be paid but provide distinction to none.
Availability of IT increased (see even at Grocery shops) and cost decreased.
More ubiquitous they are, less strategic they become.
The Commoditization of IT Makes it valuable when shared than in isolation.
IT is also highly replicable- no perfect commodity than a byte of data at virtually no cost.
Scalability of IT combined with technical standardization dooms applications to economic obsolescence.
Internet accelerated commoditization of IT by providing perfect delivery channel of apps.
IT diffuses very fast from inception to maturity. Last ten years number of WWW sites grew from 0 to 40 million.
Since 1980, over 280 million miles of fiber optic cable is installed- circle the earth 11,320 times.
Impression 3: IT capability
Because of its ability to record every customer interaction,
Ability to offer insights into customer and market behavior,
Turn a business into a scientific laboratory for pre and post-production and manufacturing purposes
Its potential to re-invent the business itself
IT’s proximity to decision making
8
IT Capability.. How IT is used rather that what of IT
is used
IT fundamentally offers two important capabilities to businesses:
Integration and
Interactivity
These capabilities have to be managed effectively for business
9
Implication 1: Integration
Enables powerful integration of various business functions : Marketing, Operations, Design , Finance (Example: ERP based systems)
Integrates both internal and external functions
Empowers suppliers and customers to become part of the extended enterprise
10
Web 2.0 Web 2.0 covers a broad range of new online
services, user-generated content, communities and social networking tools.
Examples :Blogger, Flickr, MySpace, YouTube , Wikipedia and the Godfather of web 2.0 - Google.
It is creation of far greater levels of interactivity, not just between users, or between users and the internet but between complementary online services through web services 11
Observation..
“..Ordinary people now have access to technology, where they can create value and even collaborate and level the playing field with the world’s mightiest enterprises ..
Anthony Williams, “ Wikinomics: How Mass collaboration Changes Everything”, 2007
12
Insight..
Web 2.0 takes some of its philosophical underpinning from James Surowiecki's book “The Wisdom of Crowds”, which asserts that the aggregated insights of large groups of diverse people can provide better answers and innovations than individual experts.
13
Comment..
If infrastructure is for connectivity -- akin to railroad, Integration is about integrating functionalities of various systems and applications even people; in a broad sense focused on integrating people, processes and technology in an enterprise setting.
Role of Management: Enables effective integration, provide necessary eco-system for integration
14
Implication 2: Interactivity
Interactivity (WAP, Web Services, XML) being more recent in the IT evolution
Enables to understand customer better
Establishes long term relationships with both customer and suppliers
Helps in understanding product features and add-ons by close interaction
15
Implication..
Ever since the Internet brought down the cost of connectivity, the need for integration (be it application integration, b2b integration or data integration) has been growing
So also interactivity needs of enterprises particularly dealing with bringing in pervasive functionalities as in enterprise mobility, personalisation and so on
16
Part 2
Evaluation of Coordination in supply chain- A Soft Computing Approach
Supply Chain Coordination
Act of working together and managing dependencies among activities (Malone and Crowston, 1994)
Integration or linking together of different parts of an organization to accomplish a collective set of tasks (Van de Ven et al., 1976)
Coordination is a process to bring into a common action, movement or condition, or to act together in a smooth concerted way (Mattessich et al., 2001)
19
Soft Computing
Soft computing is an umbrella term for a collection of computing techniques
It is tolerant of imprecision, uncertainty and partial truth
Models based on human reasoning.
Models can be - linguistic, - simple (no number crunching), - comprehensible (no black boxes), - fast when computing,
- good in practice.
.
20
Soft Computing Applications : Business
• supplier evaluation customer targeting, • sequencing, • scheduling, • optimizing R&D, • projects, • knowledge-based prognosis, • fuzzy data analysis
• hospital stay prediction, • TV commercial slot evaluation, • address matching, • multi-criteria optimization, etc. •Supply Chain Coordination
Need of Coordination The supply chain entities optimize their local
objectives without taking into account its effect on whole supply chain performance
These conflicting objectives result in more inventory held up,
increased system wide costs,
more uncertainty and
more demand fluctuations
To improve the performance of whole supply chain these conflicting issues are required to be resolved by coordinating the supply chain processes
How supply chain coordination can be achieved?
Effective Implementation of coordination mechanisms is a
good indicator of coordination
Extent of coordination may be represented as a function of i
coordination mechanisms (CM)
EC= f (CM1, CM2, CM3, .......... CMi)
A soft computing based model is proposed to evaluate EC:
Fuzzy based Analytic Hierarch Process (FAHP)
Contracts • Structured at beginning of relationship • Decisions regarding risks and rewards • Set foundation for the adoption of other mechanisms • Optimal decisions do not satisfy all members of supply chain • Sort out conflicts and confusions • Reduces uncertainties and encourage long term partnerships
• Comprised of quantity, price, cost and demand
Information Sharing • Type of information shared • Willingness to share information • Improve different performance measures like reduce supply chain costs, inventory levels, demand variance, lead time and greater customer satisfaction • Reduces uncertainty in supply and demand
Information Technology • Type of information system • Speed and accuracy of information
system • SCM/ERP software • Mode of communication
Joint Decision Making • Joint planning • Joint forecasting •Joint replenishment • Joint ordering • Joint benefit sharing
SUPPLY CHAIN COORDINATION
Coordination mechanism- Information Sharing
Order information
Inventory data
End customer demand
Sales data
Capacity
Production schedule
Lead time
Price scheme
Status of order
Product quality
Future plans
New technologies
Product specifications
Coordination mechanism- Information Technology
Precise and accurate information flow
Faster and cheaper order processing
Reduces uncertainty
Increase flexibility
Improves customer service
Reduces response time
Extent of coordination (EC)
EC = w1*CO + w2*IS + w3*IT + w4*CL
where w1, w2, w3, w4 are relative weights of four coordination mechanisms
CO, IS, IT and CL are the crisp scores of four mechanisms i.e contracts, information sharing, information technology and collaboration respectively
The crisp scores are assessed by defuzzyfying the linguistic terms representing these factors
EL VL L SL AV SH H VH EH
1 0
0 0.2 0.4 0.6 0.8 1.0
Degre
e
of
mem
be
rship
a b c d
SH H VH
a b c d
112
1
ab
b
dc
dC
Linguistic terms assigned to coordination mechanisms Conversion of fuzzy to crisp number
Crisp scores CSCO: Contracts, CSIT: Information technology, CSIS: Information sharing and CSJD: Joint decision making
Pair wise comparisons of coordination mechanisms
Relative weights of coordination mechanisms
Check for consisten
cy
Relative weights for Contracts, Information technology, Information sharing and Joint decision-making respectively
JDISITco ωandω,ω,ω
Inconsistent
Consistent Extent of Coordination JDJDISISITITCOco CSωCSωCSωCSωEC +++=
FAHP model
AHP
Outcomes of FAHP model
Uniform linguistic terms to coordination mechanisms
Easiness of assigning linguistic terms by managers
Extent of coordination based on the implementation and importance of coordination mechanisms
Applied to a real life case study
7701570770287068051407700420 .*.+.*.+.*.+.*.=EC
= 0.724
Low
1 0 0 0.3 0.4 0.7
0.86
Medium High
Score for Extent of Coordination
Degree of membership
Pairwise comparison score
Coordina-
tion by
Contracts Information
Sharing
Information
Technology
Collaboration
Contracts 1 a12 1/a31 a14
Information
Sharing 1/a12 1 a23 1/a42
Information
Technology a31 1/a23 1 1/a43
Collabor-
ation 1/a14 a42 a43 1
Analytic Hierarchy Process (AHP)
Set AHP subjective scale for pair wise comparison of factors on the basis of their relative importance
Normalize the comparison scores
Calculate the relative weights by taking average of normalized scores and assign as w1, w2, w3 and w4 for contracts, information sharing, information technology and collaboration respectively
The defuzzification process is done using the conversion formula given by Chen and Hwang (1992).
Where C is the crisp number computed by using trapezoidal membership fuzzy number M= (a,b,c,d)
112
1
ab
b
dc
dC
Input data for DSTSCC for two level SC (A) Data considered for numerical example Cost (cs) : 12 Cost (cb) : 2 Salvage (ss) : 9 Salvage (sb) : 10 Goodwill cost (gs ) : 8 Goodwill cost (gb) : 14 Wholesale price (w) : 20 Price of product (p) : 30 Demand ~ N (100, 302) (B) Decision variables for numerical example Optimal order quantity : 111.35 units : 139.35 units
Other variables: : 15, w’ : 10.1 : 0.6 and : 0.148
Input data for DSTSCC for three level SC (A) Data considered for numerical example Level 1 Level 3 Marginal cost(cL1) : 20 Marginal cost (cL3) : 5 Goodwill cost (gL1) : 6 Goodwill cost (gL3) : 8 Salvage (sL1) : 16 Salvage (sL3) : 28 Wholesale price (w12) : 36 Price of product (p) : 60 Level 2 Marginal cost (cL2) :7 Goodwill cost (gL2) :7 Demand distribution N(100, 202) Salvage (sL2) : 17 Wholesale price (w23) : 50 The cost and price are in monetary units (B) Decision variables as Output data for DSTSCC 23 = 46 12 = 26 23 = 0.532 12 = 0.519 w’23 = 23.8 w’12 = 18.03 δ = 0.2936 Q*sc = 128.72 units
*b
Q *sc
Q
Snapshot of the Model
Supply chain
member
Expected Performance
Measures
Case I
Scenario 0 (No
Coordination)
Case II “Coordination”
Scenario 1
(Coordin-ation
with optimal)
Scenario 2
(Scenario1+
Buyback contracts)
Scenario 3
(Scenario1+
Revenue sharing
contracts)
Scenario 4
(Scenario1+
Quantity
flexibility
contracts)
•Level 3
Actual Sale 86.760 99.20 99.195 99.195 102.171
Revenue realized 5205.596 5951.72 5951.722 3166.812 6130.253
Leftover inventory 4.165 29.53 29.529 29.53 2.539
Salvage realized 116.615 826.81 1353.762 826.81 71.081
Units short 13.048 0.61 0.612 0.61 0.480
Goodwill realized 104.381 4.90 4.897 4.90 3.836
Marginal value realized 454.624 643.62 643.621 643.62 586.922
Wholesale value incurred 4546.238 6436.21 6436.207 3076.507 5869.217
Buyback quantity realized 0 99.20 1353.762 0 633.741
Expected Profits 216.969 -306.198 220.759 268.593 375.101
•Level 2
Leftover inventory 0 0 29.565 29.529 2.539
Salvage realized 0 0 568.694 0 215.472
Units short 13.052 0.924 0.924 0.612 0.480
Goodwill realized 104.415 7.391 7.391 4.897 3.836
Marginal value realized 636.473 901.068 901.068 901.068 586.922
Wholesale value realized 4546.237 6436.205 6436.206 4522.280 5869.217
Wholesale value incurred 3273.29 4634.068 4634.068 2385.040 4225.836
Buyback quantity realized 0 0 568.694 0 456.294
Buyback quantity incurred 0 0 1359.99708 0 633.741
Expected Profits 545.110 894.602 1008.675 1231.886 856.358
Performance measures for different scenarios for three level supply chain
Level 1
Leftover inventory 0 0 29.565 29.565 2.539
(Salvage realized –buyback quantity) 0 0 417.477 0 202.797
Units short 13.052 0.924 0.924 0.612 0.480
Goodwill realized 626.491 5.543 5.543 3.673 2.877
Marginal value realized 1818.494 2574.482 2574.482 2574.483 2347.687
Wholesale value
incurred 3273.290 4634.068 4634.068 4415.645 4225.836
Expected Profits 828.305 2054.043 1936.279 1081.659 1621.776
Total Expected Profits of SC 1599.022 2638.789 2638.789 3175.516 2853.235
Supply chain
member
Expected
Performance
Measures
Case I
Scenario 0 (No
Coordination)
Case II “Coordination”
Scenario 1
(Coordin-
ation with
optimal)
Scenario 2
(Scenario1+
Buyback
contracts)
Scenario 3
(Scenario1+
Revenue sharing
contracts)
Scenario 4
(Scenario1+
Quantity
flexibility
contracts)
Performance measures for different scenarios for three level supply chain (Contd.....)
Significance of coordination
mechanisms Absence of contracts
Reduces profits of buyer
Absence of Information technology
Increases units short and goodwill cost
Absence of information sharing
Increase in marginal cost of supplier and
overstock
Absence of join decision making
Reduces the profits of both supplier and buyer
Different Scenarios
Performance Measures* Scenario 2
(Buyback
contract)
Cont. to the profits
(%)* Scenario 3
(Revenue
sharing
contract)
Cont. to the
profits (%)
Scenario 4
(Quantity
flexibility
contract)
Cont. to the
profits (%)
Buyer
Revenues realized 171.03 13.8 -995.06 -45.8 171.03 34.0
Salvage realized/ (Returns
realized in Scenario 2) 375.47 30.2 223.44 10.3 39.49 7.9
Goodwill incurred 79.82 6.4 79.82 3.7 79.82 15.9
Marginal cost incurred -56.00 -4.5 -56.00 -2.6 -19.28 -3.8
Wholesale value realized -560.02 -45.1 819.08 37.7 -192.84 -38.4
Total Gain (Loss) 626.32
(-616.02)
50.4
(-49.6)
1122.34
(-1051.06) 51.6 (-48.4)
290.34
(-212.12)
57.8
(-42.2)
Supplier
Salvage realized 379.61 19.4 0 0 26.90 6.1
Goodwill incurred 45.63 2.3 45.63 6.3 45.63 10.4
Marginal cost incurred -336.01 -17.2 -336.01 -46.1 -115.70 -26.2
Wholesale value realized 560.02 28.7 347.01 47.6 192.84 43.7
Returns cost incurred -631.62 -32.3 0 0 -59.77 -13.6
Total Gain (Loss) 985.26
(-967.63)
50.5
(-49.5)
392.64
(-336.01)
53.9
(-42.1)
265.36
(-175.47)
60.2
(-39.8)
Relative contribution of different performance measures in the profit function
End Thoughts IT is a dominant technology
Smart use of technology
IT does matter by offering capabilities
Integration
Interactivity
IT as a back end tool in Soft computing
Part of decision making
Supply chain as an application domain
Evaluation of various scenarios
Evaluation of alternative scenarios
References
Arshinder Kaur, Kanda, A. and Deshmukh, S. G. (2006), “A graph theoretic approach to evaluate supply chain coordination”, International Journal of Logistics and Systems Management”, Vol. 2, No.4, pp. 329-341
Arshinder, Kanda, A. and Deshmukh, S. G. (2007), “Coordination in Supply Chains: An Evaluation using Fuzzy Logic” ,Production Planning and Control, Vol. 18, No. 5, pp. 420-435
IT doesn’t Matter: http://www.nicholasgcarr.com/articles/matter.html
Thanks
