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Amanda Johnston-Pell
Chief marketing officer and chief of
start-ups IBM Australia New Zealand
IBM Watson: “A potent way for
businesses to tap into advances in
machine learning and AI in order to
have a real impact at a commercial
level”
Seyed Roham Hosseini
28571606 1
Target Segment
Geographic (Australia)
Firmographics (Leaders of Finance and
Banking Sector)
Attitudes (Affect Performance and has
Strategy Implications)
Needs (Strategic Need (Gelderman & Weele,
2003))
61% will adapt to AI in 2018
Among 20% that are already using:
• 43% for Data Analysis
• 20% on Site Personalisation
(Lo, 2018)2
Needs
3
Diagnosing
Needs
Organizing
process and
resources
Managing
value
conflicts
Implementing
the solution
Designing and
producing the
solution
• Update IT operating model
• Slash costs by simplifying legacy systems,
taking SaaS beyond the cloud, and
adopting robotics/AI
• Technology capabilities to get more
intelligent about customers’ needs
• Adaptable architecture to connect to
anything, anywhere
• Cyber-security
• Access to the talent and skills necessary to
execute and win
Challenge
Challenges:
• Bad Image of Artificial Intelligence in the
Financial Sector (Wigglesworth, 2016)
• Machine Learning and AI requires advance
computing skills
• Big players in the field (Mint Global, 2018).
Solution:
• Using the existing brand and infrastructure
in financial sector businesses and create
Artificial Intelligence moderated ecosystem
for Financial sectors.
Outcome:
• Promotion of IBM Watson attributes for
Change Managers and IT managers
4
Multi Attribute Analysis
Attribute
Importance
(1: Low, 3: High)
AlphaSense Cerebellum Capital Dataminr IBM Watson
Robotic Process Automation
Natural Language Processing
Advanced Data Analytics
Image Analytics
Fraud Detection
Decision Support
Total
5
B2B
Thought-based
decision
Compensatory
decision
Multi Attribute
Model
Attributes Extracted from (Lin , 2018) the competitors extracted from (Butcher & Clarke, 2018)
43 47 42 47
Watson
Machine Learning
(Long-term investment)
Risk Analysis
Creating an IBM
Ecosystem
Market Intelligence
Portfolio Management
Exchange Traded Funds
Better Utilisation of HR
6
References
Aarikka-Stenroos, L., & Jaakkola, E. (2012). Value co-creation in knowledge intensive business services: A dyadic perspective on the
joint problem solving process. Industrial Marketing Management, 41(1), 15-26. doi:10.1016/j.indmarman.2011.11.008
Butcher, S., & Clarke, P. (2018, May 05). 7 finance firms working with AI, and why you should fear them. Retrieved from
https://news.efinancialcareers.com/au-en/270262/ai-in-finance
Chan, G. (2017, May 22). Artificial Intelligence for Customer Engagement -IBM's Watson and the development of a unique value
proposition. Retrieved September 5, 2018, from https://researchandinnovationportsmouth.com/2017/05/22/artificial-intelligence-
for-customer-engagement-ibms-watson-and-the-development-of-a-unique-value-proposition/
IBM. (2017, October 15). IBM Watson. Retrieved September 5, 2018, from https://www.ibm.com/watson/
Gelderman, C. J., & Weele, A. J. (2003). Handling measurement issues and strategic directions in Kraljics purchasing portfolio model.
Journal of Purchasing and Supply Management, 9(5-6), 207-216. doi:10.1016/j.pursup.2003.07.001
Lin, M. (2018). How Artificial Intelligence Is Disrupting Finance. Retrieved September 5, 2018, from
https://www.toptal.com/finance/market-research-analysts/artificial-intelligence-in-finance
Lo, B. (2018). IBISWorld Industry Report J5921 Data Processing and Web Hosting Services in Australia. IBISWorld.
Mint Global. (2018). company report of IBM AUSTRALIA LTD. Mint Global. Mint Global.
PwC. (2016). Financial Services Technology 2020 and Beyond: Embracing ... Retrieved September 5, 2018, from
https://www.pwc.com/gx/en/financial-services/assets/pdf/technology2020-and-beyond.pdf
Rayome, A. D. (2018, June 21). Exclusive: 61% of financial services companies will use AI this year. Retrieved September 5, 2018, from
https://www.zdnet.com/article/exclusive-61-of-financial-services-companies-will-use-ai-this-year/
Weinstein, A. (2004). Handbook of market segmentation: Strategic targeting for business and technology firms. Mumbai: Jaico
Publishing.
Wigglesworth, R. (2016, March 25). AI progress fails to convince all investors. Retrieved September 5, 2018, from
https://www.ft.com/content/1c249b10-ed49-11e5-888e-2eadd5fbc4a4 7

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Buyer's Behaviour Pitch for chapter Decision Making and Judgment on IBM Watson

  • 1. Amanda Johnston-Pell Chief marketing officer and chief of start-ups IBM Australia New Zealand IBM Watson: “A potent way for businesses to tap into advances in machine learning and AI in order to have a real impact at a commercial level” Seyed Roham Hosseini 28571606 1
  • 2. Target Segment Geographic (Australia) Firmographics (Leaders of Finance and Banking Sector) Attitudes (Affect Performance and has Strategy Implications) Needs (Strategic Need (Gelderman & Weele, 2003)) 61% will adapt to AI in 2018 Among 20% that are already using: • 43% for Data Analysis • 20% on Site Personalisation (Lo, 2018)2
  • 3. Needs 3 Diagnosing Needs Organizing process and resources Managing value conflicts Implementing the solution Designing and producing the solution • Update IT operating model • Slash costs by simplifying legacy systems, taking SaaS beyond the cloud, and adopting robotics/AI • Technology capabilities to get more intelligent about customers’ needs • Adaptable architecture to connect to anything, anywhere • Cyber-security • Access to the talent and skills necessary to execute and win
  • 4. Challenge Challenges: • Bad Image of Artificial Intelligence in the Financial Sector (Wigglesworth, 2016) • Machine Learning and AI requires advance computing skills • Big players in the field (Mint Global, 2018). Solution: • Using the existing brand and infrastructure in financial sector businesses and create Artificial Intelligence moderated ecosystem for Financial sectors. Outcome: • Promotion of IBM Watson attributes for Change Managers and IT managers 4
  • 5. Multi Attribute Analysis Attribute Importance (1: Low, 3: High) AlphaSense Cerebellum Capital Dataminr IBM Watson Robotic Process Automation Natural Language Processing Advanced Data Analytics Image Analytics Fraud Detection Decision Support Total 5 B2B Thought-based decision Compensatory decision Multi Attribute Model Attributes Extracted from (Lin , 2018) the competitors extracted from (Butcher & Clarke, 2018) 43 47 42 47
  • 6. Watson Machine Learning (Long-term investment) Risk Analysis Creating an IBM Ecosystem Market Intelligence Portfolio Management Exchange Traded Funds Better Utilisation of HR 6
  • 7. References Aarikka-Stenroos, L., & Jaakkola, E. (2012). Value co-creation in knowledge intensive business services: A dyadic perspective on the joint problem solving process. Industrial Marketing Management, 41(1), 15-26. doi:10.1016/j.indmarman.2011.11.008 Butcher, S., & Clarke, P. (2018, May 05). 7 finance firms working with AI, and why you should fear them. Retrieved from https://news.efinancialcareers.com/au-en/270262/ai-in-finance Chan, G. (2017, May 22). Artificial Intelligence for Customer Engagement -IBM's Watson and the development of a unique value proposition. Retrieved September 5, 2018, from https://researchandinnovationportsmouth.com/2017/05/22/artificial-intelligence- for-customer-engagement-ibms-watson-and-the-development-of-a-unique-value-proposition/ IBM. (2017, October 15). IBM Watson. Retrieved September 5, 2018, from https://www.ibm.com/watson/ Gelderman, C. J., & Weele, A. J. (2003). Handling measurement issues and strategic directions in Kraljics purchasing portfolio model. Journal of Purchasing and Supply Management, 9(5-6), 207-216. doi:10.1016/j.pursup.2003.07.001 Lin, M. (2018). How Artificial Intelligence Is Disrupting Finance. Retrieved September 5, 2018, from https://www.toptal.com/finance/market-research-analysts/artificial-intelligence-in-finance Lo, B. (2018). IBISWorld Industry Report J5921 Data Processing and Web Hosting Services in Australia. IBISWorld. Mint Global. (2018). company report of IBM AUSTRALIA LTD. Mint Global. Mint Global. PwC. (2016). Financial Services Technology 2020 and Beyond: Embracing ... Retrieved September 5, 2018, from https://www.pwc.com/gx/en/financial-services/assets/pdf/technology2020-and-beyond.pdf Rayome, A. D. (2018, June 21). Exclusive: 61% of financial services companies will use AI this year. Retrieved September 5, 2018, from https://www.zdnet.com/article/exclusive-61-of-financial-services-companies-will-use-ai-this-year/ Weinstein, A. (2004). Handbook of market segmentation: Strategic targeting for business and technology firms. Mumbai: Jaico Publishing. Wigglesworth, R. (2016, March 25). AI progress fails to convince all investors. Retrieved September 5, 2018, from https://www.ft.com/content/1c249b10-ed49-11e5-888e-2eadd5fbc4a4 7