Synopsis:

Big Data and predictive analytics have become important parts of the business strategy and operational capabilities for a growing number of organizations. Neural networks and artificial intelligence are currently deployed by a number of governments, financial institutions, insurance companies and manufacturers and more general adoption appears inevitable. However, effectively realizing the potential of these extremely powerful technologies in individual projects is often problematical. Moreover, leveraging them more broadly in domains such as strategy, logistics, financial planning, organizational structure and corporate culture is woefully lacking in general.

In part, this arises because of a fundamental misunderstanding about the nature of these technologies. Some organizations cannot readily adapt to their “fuzzy” aspects or recursive nature or research (rather than end product) orientation. In part, difficulties arise due to management’s unrealistic expectations, or the use of inappropriate or outmoded metrics to measure success. Mostly, management sees these technologies as “solutions”, rather than sophisticated support tools intended to enable better and faster decision making.

For the Project Manager, these areas represent both a significant challenge as well as a ground floor opportunity!

Our presentation will provide participants with:

• introduction to the relevant technologies and underlying math (a little 😊);
• exploration of the special skills needed to build truly smart and sophisticated, data-driven systems and models;
• examples of successful incremental and transformational projects actually deployed today;
• overview of evolving project management best practices in the area (standards, methodologies, resources);
• tips and suggestions about putting together an effective big data/analytics/neural network/AI team;
• guidance in developing a “high tech” business case with the proposed end user or business owner; and
• a look into the future at the changing role of the PM and new opportunities arising.

The presentation will also include an in class, group case study ( 45 - 60 minutes).

Learning Objectives:

• Identify and better understand the critical success factors underlying high tech projects
• Recognize potential issues and problems (risks) with high tech projects at an early stage of development and formulate corrective action
• Improve team building, management, oversight and evaluation skills
• Identify third party standards and best practices and adapt to the project at hand
• Articulate key differences between data warehousing, business intelligence and high technology projects in so far as best project management techniques
• Better understand the underlying value proposition in high tech projects
• Learn a few useful rules-of-thumb to perform a high level review of statistical modelling without getting lost in statistics
• Update your understanding of big data, analytics, neural networks and artificial intelligence, including capabilities, limitations, costs & benefits, risks & opportunities
• Communicate more effectively with senior management, IT, data scientists and business sponsors in matters of Big Data and predictive analytics, including through the project planning / business case development process

Biography:

Jerry Gaertner is President at Managed Analytic Services Inc. (MAS), a company which he co-founded in 2012. Through MAS, Jerry provides big data solutions, consulting and implementation services in the area predictive analytics. He also provides consulting services in the areas of risk & compliance, continuous audit, IT governance & strategy. Jerry regularly advises start-up companies and is an Angel investor himself.

In the realm of higher education and not-for profit, Jerry is Adjunct Professor of Computer Science at Ryerson University (pending re-appointment) where he teaches computer security and law (graduate level) and digital forensics. He is lead instructor and co-developer of U. of T.’s highly successful Big Data certificate programme. Jerry is Executive Director of the Digital Legacy Institute and past President of the Canadian Information Processing Society (CIPS). He is a former Board member of the Association of Certified Forensics Investigators and of the Ontario Association of Insolvency and Restructuring Practitioners.

Jerry is author of three books and a graduate of MIT. Prior to founding his current company, he held senior positions for over 25 years in “Big 4” and “Big 10” international accounting firms.

Jerry is accredited as a chartered professional accountant (CPA), and is certified in Fraud and Forensics (CFF), Information Technology (CITP), Governance of Enterprise IT (CGEIT), as an Information Systems Security Professional (CISSP), Information Privacy Professional (CIPT), Internal Auditor (CIA), Forensic Investigator (CFI) and Information Systems Professional (I.S.P.).

Agenda:

8:30am - 8:45am  GTIS/PMI introduction

8:45am - 10:15am  Presentation/Open discussion

10:15am - 10:30am  Break

10:30am - 12:30pm  Presentation/Workshop/Open discussion

Fees: (subject to HST)

PMI Toronto Members - $50.00
Non-Members and Guests - $70.00

PDUs: 4.0 (Technical 2.0, Leadership 1.0, Business 1.0)