Member Summit 2016 - Session Abstracts

Opening Keynote: Driving Motorola Solutions’ Digital Transformation with Innovation through Data

Eduardo Conrado, Executive Vice President, Strategy & Innovation Office
Paul Steinberg, Senior Vice President, Chief Technology Officer

Motorola Solutions is transforming from providing communications equipment to delivering next-generation software and services. As the 88-year-old company develops innovative solutions for customers ranging from police departments to multinational petrochemical companies, it is using a combination of customer-focused research and data science to understand and meet customer needs, and then advancing those solutions using an open innovation approach.  

Conrado and Steinberg share insights into the role of big data in Motorola Solutions’ evolution. Discover how design thinking and data science inform solution development, creating a culture of data collection, evolving the business model and cultivating the right skill sets for data-driven innovation. They’ll also share examples of Motorola Solutions’ approach in action.

Digitalization Report Out: Big Data 

Jeffrey Alexander, PhD, Senior Manager, Innovation Policy, RTI International
Michael (Mike) Blackburn, MS, ThD, Portfolio/Program Leader, Cargill Global Research Management 
Diego Klabjan, PhD, Professor, Department of Industrial Engineering and Management Sciences, Director, Master of Science in Analytics, Northwestern University

The Big Data project is part of IRI’s strategic research platform on Digitalization and its Implications for R&D Management. The goal of the study is to validate the hypothesis that digitalization will impact R&D Management.  Our research framework has asked the questions:
•    How will Big Data inform R&D activities?
•    How will Big Data enable new R&D activities?
•    How will Big Data disrupt traditional R&D?
In the evaluation of these questions we have considered the impact on strategy, people, technology and process integration.  This presentation includes the findings of this study and a discussion of what R&D management needs to do to prepare for a digitalized future.

Digitalization Report Out: Augmenting R&D Innovation through Collaborative Crowdsourcing

Stephanie Orellana, Vice President - Service Delivery, NineSigma, Inc. 
Terry L. Rosenstiel, Director, Partnerships and Innovation Pipeline, USG Corporation
Hila Lifshitz-Assaf, Assistant Professor of Information Systems, Management & Organizations, NYU, Stern School of Business, Faculty Associate, Berkman Center for Internet and Society, Harvard University
Felicia Ng, Graduate Research Assistant, Human-Computer Interaction Institute, Carnegie Mellon University

Innovation in R&D is a perpetual challenge, but online crowdsourcing platforms have enabled unprecedented opportunities to find creative inspirations and spark novel connections between ideas from diverse sources. Learn how the ROR Collaboration team leveraged the power of new crowdsourcing tools in combination with scientifically-proven strategies for creative thinking to develop a new method for augmenting R&D problem solving. The team will reveal findings from the first ever field test of this new process, conducted at the IRI Spring Networks Meeting and Annual Meeting, to solve two real industrial challenges, and what the results imply about emerging best practices for augmenting R&D innovation. 

Digitalization Report Out: Virtual Experimentation & Simulation 

Steve Moskowitz, Senior Principal, Innovation Management, Entegris
AJ Rao, PhD, Senior Researcher, Building Science & Technology Commercialization, USG
Anita Friis Sommer, PhD, Senior Consultant, Continuous Improvement, The LEGO Group

Investment in Virtual Experimentation and Simulation (VE&S) in R&D is growing rapidly across industries. Technology has matured and investment barriers are decreasing to tolerable levels.  However, these are still early days, and we have yet to see the full potential of VE&S. Therefore, it is important to get a reading on best practices and pitfalls from early adopters. Hear the preliminary results of an ongoing study by the VE&S in R&D research team. The research plan for this study captured information around the evolution of VE&S use in organizations, best practices for adoption, as well as opportunities for the future. This was done through a comprehensive literature review, one-on-one interviews with practitioners, and a broad ranging survey of member organizations. As the study nears its completion, it has already uncovered many interesting insights. Learn the best practice findings from the literature review including specific case studies, analysis of the survey data, as well as insights from a maturity matrix that was developed to capture results from the interviews.  

Past, Present, and Future of Simulation at John Deere - Case Study

Emily Horn, Manager, Simulation & Analysis, Deere & Company

Track the history of simulation and analysis at Deere & Co. and hear about Deere’s vision for the near and far futures.  Current analysis activities at John Deere are focused on verification and validation of intermediate or final designs usually at a component or sub-system level.  Models tend to be single-use and are created manually.  Multi-physics and multi-discipline models are rare and difficult to create and solve.  To continue delivering quality, high performing machines in the future an integrated, automated digital ecosystem will be required to truly achieve model-based systems engineering (MBSE).  

Simulations will be vital in determining requirements, synthesizing designs, and these performance models will be treated as IP assets similar to 3D CAD.  Model-based design has been present for some years, but with the increasing complexity of our machine systems MBSE is necessary to help our design engineers succeed at managing complexity, changing requirements, emergent behavior, and competing multi-discipline objectives.  John Deere’s journey to enabling MBSE includes both technology development and a cultural shift of how work is performed.

Using People Analytics to Accelerate Innovation: Techniques for Data-Driven R&D Talent Management - Case Study

William Pike, Director, Computational and Statistical Analytics (CSA) Division, Pacific Northwest National Laboratory (PNNL)

R&D organizations depend on the right mix of human talent to drive innovation.  But the alchemy involved in aligning individuals and teams for success is often poorly understood, and early recognition of promising advances or critical blockers depends heavily on intuition.  At the same time, modern organizations can be extraordinarily well instrumented, providing a rich set of data sources that can be mined to better recruit, retain, engage, and integrate R&D teams.  The same big data analysis techniques that are applied to the object of an R&D activity can now be applied to the R&D process itself, helping decision makers move beyond reliance on hunches and prior experience and instead gain deep insight into the conduct of research, spot emerging innovation opportunities early, and reveal the key characteristics of high-performing innovation teams.  

Participants explore a suite of data analysis methods and tools – including large graph analysis of internal collaboration networks, centrality measures to identify hidden influencers and bridge builders, and machine learning algorithms for predicting innovation performance – that have been used inside a research organization to gather, synthesize, and extract insight from large, complex, and heterogeneous data about the organization itself.  Discuss lessons learned in how these approaches should be implemented, what tools and software can assist, and how to assess the impact of these new methods.

Keep Cool. Innovation Contests & Hershey - Case Study

Dr. Eloise Young, Senior Program Manager, NineSigma 

The Hershey Company was looking for solutions to a longstanding issue – keeping chocolate cool during shipment in warm weather. In early 2016, the company engaged NineSigma to issue a global technology search for solutions. The Hershey Cool Ship Technologies Contest sought lightweight, affordable shipping system solutions that would keep chocolate close to the temperature at which it was packed, 75°F or below, for at least 48 hours. The ultimate goal of the Contest was to develop a system that would be inexpensive enough to use year round, as part of the standard packaging for small parcel shipments. This case study presentation will look at the process behind the Contest, outcomes, and the challenges encountered along the way. 

Progress in Fire Protection VE&S at FM Global - Case Study

Sergey B. Dorofeev, PhD, Assistant Vice President, Director of Fire Hazards and Protection Research, FM Global

FM Global Fire protection standards have largely been developed to date by conducting large-scale fire tests. These standards are not fixed and have to be updated as evolving buildings, materials and industrial facilities challenge existing fire protection designs. Often large-scale fire testing becomes prohibitively expensive or impossible to conduct at the actual scale in the existing fire testing facilities. In this situation, Virtual Experimentation and Simulation (VE&S), which describes fire behavior and fire protection on the basis of predictive physical models, has become attractive as a needed alternative and complement to fire testing. A strategic fire modeling program was initiated within the Research Division at FM Global with significant investment in staff and scientific computing. The modeling effort is based on the development of an open-source Computational Fluid Dynamics (CFD) code. The open-source concept has allowed for wide cooperation with academia and industry to address an extremely challenging modeling scope involving multiple physics in fire growth and fire suppression phenomena. Since the 5th year of the program initiation, fire protection VE&S has become increasingly mature for practical applications gradually replacing the trial-and-error paradigm in fire protection design. The quality of solutions developed at FM Global has further improved, resulting in more timely, efficient, and affordable fire protection options. The challenges, progress, and benefits of this fire modeling effort will be discussed. 

Exploring the Benefits and Challenges of Crowdsourcing Innovation - Case Study

Stephanie Orellana, Vice President - Service Delivery, NineSigma, Inc. 
Terry L. Rosenstiel, Director, Partnerships and Innovation Pipeline, USG Corporation
Hila Lifshitz-Assaf, Assistant Professor of Information Systems, Management & Organizations, NYU, Stern School of Business, Faculty Associate, Berkman Center for Internet and Society, Harvard University
Felicia Ng, Graduate Research Assistant, Human-Computer Interaction Institute, Carnegie Mellon University

In an interactive follow-up session to their plenary talk, the ROR Collaboration team will delve deeper into their latest research on a new crowdsourced innovation process for augmenting R&D problem solving, and reveal more details from the first ever field test of the process that was conducted at the IRI Spring Networks Meeting and Annual Meeting. Find out how two real industrial problems were solved by IRI members with the help of inspirations from online crowds and what the results reveal about emerging best practices for problem formulation and creative ideation when exploring a solution space for R&D challenges. Join us to discuss the benefits and challenges learned from the field tests, and explore how you can use crowdsourcing to augment R&D problem solving in your organization.

 

RTI and Online Analysis - Case Study

Ian Thomas,Research Data Scientist I, Division for Statistical and Data Sciences, RTI

As the demand for web-based analytics increases, more and more software and web applications are appearing on the market every day.  This begs the question of when is it better to buy and when is it better to build? To make public data from their sponsored surveys more accessible and easier to work with, the Substance Abuse and Mental Health Services Administration (SAMHSA) worked in combination with RTI on survey statistics, data visualization, and data engineering.  Learn more about the architecture, technical decisions, and the design process RTI used to build the Substance Abuse and Mental Health Data Archive (SAMHDA) Data Analysis System (DAS) tool. 
 

Future of Digitalization Panel Discussion 

Join research team leaders to discuss different views on how digitalization will change business models and impact all aspects of the innovation process. What are the trends to identify now that might reshape your business?  Bring your questions.

Anita Friis Sommer, PhD, Senior Consultant, Continuous Improvement, The LEGO Group
Diego Klabjan, PhD, Professor, Department of Industrial Engineering and Management Sciences, Director, Master of Science in Analytics, Northwestern University

Moderated by: Ted Farrington, IRI Emeritus

 

How will Digitalization Inform, Enable, and Disrupt R&D in the Near Term?

Join your colleagues for this interactive session that will enable you to work with SMEs and members of the Big Data, Collaboration, and Virtual Experimentation & Simulation teams to determine the effects of these advances on your industry.  Attendees will be divided into three groups and will have a chance to rotate between all three of the Digitalization topics (Big Data, Collaboration, and Virtual Experimentation & Simulation), examining how each will inform, enable and disrupt R&D strategy, people, technology, and process integration.  You will leave with a better understanding of how to effectively plan to integrate these technologies into your business.

 

Keynote: The 21st Century Brilliant Factory

Stephan Biller, PhD, Chief Manufacturing Scientist, GE Global Research

Imagine a factory that never stops and is constantly re-inventing itself to continuously improve products and how they are made.  Enabled by a digital thread that weds virtual tools with physical tools and connects every part of the manufacturing supply chain from product designers to factory floor workers, the factory will employ technologies like 3D printing and crowdsourcing to revolutionize product designs and speed up development timelines
Discuss GE’s vision for the Brilliant Factor and how manufacturing will be transformed as “Big Iron” meets “Big Data.” 

 

Keynote: Top 10 Critical Trends in Human Capital Management
Theresa Garcia, Sr. Organization Effectiveness Advisor, Talent & Leadership, Boeing 

Theresa Garcia highlights top trends that talent management leaders need to know to build responsive Human Capital Management strategies including, the Hollywood Model, MOOG’s, Crowdsourced Funding, Augmented Humans, the Era of Women, Cognitive Computing, Open Innovation, Innovation Ecosystems, the End of the Patent, and the intelligent, workplace Avatar. Join us for provocative discussion as we introduce  IRI’s next strategic research platform on Human Capital Management.

Liquid Talent Toolkit - Breakout
With new recruits planning to only stay at organizations for a short period and lifers considering partial retirement, how can an R&D organization effectively plan for the competencies that will be needed now and in the long term? 
Questions to be considered:
1.    How do companies redefine organizational knowledge?  
2.    What are the effects on workforce planning?
3.    What skills will leaders need to manage this type of workforce?
4.    What role can/should virtual technologies play?

Recruiting and Retaining Early Career Talent - Breakout
Questions to be considered:
1.    How can a desire for early management exposure be achieved for technical recruits?
2.    How can R&D provide opportunities for horizontal and vertical growth?
3.    How can R&D organizations recruit the best and the brightest to unsexy fields?

Career Paths for Innovation - Breakout
Can we identify a model career path for innovators?
Questions to be considered:
1.    Is the innovation career path a dead end?
2.    What constitutes the right exposure and experiences?

Effective Performance Reviews for R&D - Breakout
Questions to be considered:
1.    How effective is continuous feedback?
2.    What role can data analytics play?
3.    How can failure (from good experiments) and learning be encouraged in a performance review system?
4.    What are appropriate appraisals for innovators and those working on differing cycle times? 

 

Holland Award Address: Improved Product Development Performance Through Agile/Stage-Gate Hybrids

Anita Friis Sommer, Christian Hedegaard, Iskra Dukovska-Popovska, Kenn Steger-Jensen 

Product development at manufacturing companies is increasingly complex. Linear product development processes, including the traditional Stage-Gate process, cannot support the iterative cycles and external collaboration that characterize today’s product development efforts. Hybrid processes combining elements of Agile and Stage-Gate models offer a more flexible alternative to conventional systems. A comparative case study of seven technology-intensive companies shows how combining Stage-Gate models, at the strategic level, with the Agile method Scrum, implemented at the execution level, can offer performance improvements and other advantages over even improved Stage-Gate processes. The key contribution of this study is a generic Agile/Stage-Gate hybrid process based on best practices as identified in the case companies.

 

Lean Startup in Large Organizations
ROR Stage:  gathering and analyzing data
Lean Start-Up is a new process for product development that can enhance the stage gate process and is more suitable for developing products when there is high uncertainty in the market and/or technology – characteristics that typically occur in transformational and disruptive innovations. The lean start-up methodology had its beginnings in small companies (Eric Reis, The Lean Start-Up, Crown Publishing, 2011; Steve Blank, What the Lean Start-Up Changes Everything, HBR, May 2013). Large companies such as GE, Goodyear, and Intuit have begun to adopt the process. As large companies are fundamentally different than start-ups, the methodology, practices, pitfalls and lessons from small start-ups will have limited applicability to large companies. Accordingly, the purpose of this ROR is to learn how lean start-up is actually used in large companies, which industries it might easily be applied to and which industries need to modify and adapt the process (for example, heavily regulated industries such as medical may have difficulty with early prototyping), the implementation methodology, best practices, and lessons learned. 

Adding Sustainability to the NPD Toolbox
ROR Stage:  gathering and analyzing data
This project aims to overcome the gap between a high level view on the importance of sustainability to a “how to do it” approach to integrating sustainability into the NPD process.  The team will use the literature and a brief survey to help identify examples of success and failure and why.  
This will be followed by select interviews with companies in different business cases and in different phases of the sustainability model to identify what worked, what didn’t, and ultimately to propose tools for best practices and check lists to help companies successfully integrate sustainability into their NPD processes.

Developing & Monetizing a Long-term Vision for R&D 

ROR Stage:  gathering and analyzing data 
The goal of this ROR is to discover best practices for establishing a long-term vision for R&D that is tied to business strategies and how to use this vision to influence the strategy and direction of the firm.  The team’s hypothesis is that R+D leaders must often make investments that extend beyond the normal business planning cycle, however, insights to guide these longer term R&D investments are often challenging for organizations.  While organizations may have many of the pieces needed to form a long-term vision – such as market trends, voice of the customer, and customer and market insights – they lack critical pieces that will inform and justify longer term investments.  Participants in this ROR will learn how companies are filling those gaps in long-term insights and how they are bringing the pieces together to form a compelling vision and translating this vision into actionable steps to guide long term R&D strategy.  They will also gain best practices in terms of communicating the vision and driving organizational alignment, with the objectives being to support and influence the long-term vision for the businesses and company as a whole.  A maturity model will also be developed to enable companies to better understand the journey to strengthening their vision capabilities.   

Product Design for Mass Customization
ROR stage:  gathering and analyzing data
Customer demand for individually configured and customized products is on the rise across all industries. Companies are faced with the challenge of maintaining cost and quality while producing customized products with heightened response to individual customer needs. This project will use a breadth of approaches and the maturity of IRI members (and beyond) to determine best practices that achieve design for customization while identifying common pitfalls. The objective of the project is to understand the design implications of mass customization on manufacturers/producers by answering the following questions:
•    How do manufacturers/producers set up the architecture/platform to get to a place where they have effective mass customization?
•    How do we develop a robust, yet flexible, architecture that accommodates the evolution of the product line?
•    What are best practices and constraints/inhibitors in executing modularity and reducing complexity - balancing an optimized product?

The Aftermarket is an Afterthought:  Increasing the value R&D can deliver to customers through aftermarket innovation
ROR stage:  exploration
Currently New Product Development processes and innovation investments assume that product itself will generate customer value or deliver a distinctive customer experience. In reality, the product in itself does not add value to our customers—its use over the lifecycle does. Yet companies often leave the use experience in the hands of the customer himself, or loosely supported by distribution channels. Limited effort is directed to innovating in the aftermarket.

As increasingly sophisticated products require more customer hand holding to achieve a distinctive customer experience — leading to repurchase – designing the use experience and supporting services becomes key for business success. The best opportunity to develop aftermarket offerings to support the product is during the product development itself.

This project intends to answer the question: what are the key modifications to traditional innovation and new product development activities that would extend the focus towards the use cycle as opposed to just the product itself. The study would look for current member practices, successes and gaps, and identify key success factors in NPD that would drive a successful aftermarket service and support plan. These findings will be the basis for a checklist or consideration list that members could use to assess their processes and portfolio priorities.

Growth outside the Core
ROR stage:  organization
This project is seeking to identify (a) the specific best practices that IRI member companies use to identify whitespace opportunities and (b) actions successful organizations take to overcome barriers to commercializing these opportunities.  Likely barriers include lack of: relevant IP, appropriate business model, effective supply chain, subject matter experts, and senior management confidence in their ability to make a decision in a new area.  In some cases, an organization’s greatest asset when operating inside the core is actually an impediment to success outside the core.

The team will use roundtables of individuals from IRI member companies, case studies, and workshops held at IRI meetings to answer these questions.  The results will be reported out at IRI meetings and through an RTM journal article.
 

Closing Keynote
Steven Fifita, Executive Director, City Digital