Generating Actionable, Data-Rich Insights about Technology, Markets, and Business Models to Optimize Strategic Impact in Rapidly Expanding and Changing Environments
Applying TQM and the Toyota Production System in Development of Software Arti...Dave Litwiller
Adapting TPS Tools and Techniques for Enterprise TQM to Software, Artificial Intelligence, Machine Learning and Deep Learning Development Organizations
Business Process Improvement - A Strategic and Supply Chain Perspective Amit Kapoor
A short session I conducted at IIM Bangalore on sharing my experience on the what, how and why of business process improvement in strategy and supply chain. Credit for the concepts (and charts) go to my time spent at Booz & Company in Europe doing most of this work.
Introduction to Business Process ManagementAlan McSweeney
Training Course - Introduction to Business Process Management
It is intended to be a good general and practical introduction to the subject. It covers the following topics:
1. Business Process Management
2. Process Modelling
3. Process Analysis
4. Process Design
5. Process Performance Management
6. Process Transformation
7. Process Management Organisation
8. Enterprise Process Management
9. Business Process Management Technologies
10. Business Process Management and Business Analysis
11. Business Process Management Technology Review
Applying TQM and the Toyota Production System in Development of Software Arti...Dave Litwiller
Adapting TPS Tools and Techniques for Enterprise TQM to Software, Artificial Intelligence, Machine Learning and Deep Learning Development Organizations
Business Process Improvement - A Strategic and Supply Chain Perspective Amit Kapoor
A short session I conducted at IIM Bangalore on sharing my experience on the what, how and why of business process improvement in strategy and supply chain. Credit for the concepts (and charts) go to my time spent at Booz & Company in Europe doing most of this work.
Introduction to Business Process ManagementAlan McSweeney
Training Course - Introduction to Business Process Management
It is intended to be a good general and practical introduction to the subject. It covers the following topics:
1. Business Process Management
2. Process Modelling
3. Process Analysis
4. Process Design
5. Process Performance Management
6. Process Transformation
7. Process Management Organisation
8. Enterprise Process Management
9. Business Process Management Technologies
10. Business Process Management and Business Analysis
11. Business Process Management Technology Review
Getting Good And Staying Good At (Out)SourcingAlan McSweeney
There is an increasing and continuing trend of organisations moving from in-house solution delivery to sourcing solutions externally. Organisations are divesting themselves of what they see as non-core functions. This is intended to improve operational efficiencies by using external suppliers’ perceived abilities to provide cost-effective, fit-for-purpose solutions quickly using the right technology. The responsibility and accountability for solution delivery and operation stills lies with the acquiring organisation. An organisation’s outsourcing zone of opportunity represents a challenge for both suppliers and for the acquisition function. Learn lessons from the experience of others to define exactly what you want of your outsourcing arrangement.
5 Step Playbook to Designing and Building the Dental Practice of Your DreamsDesign Ergonomics, Inc.
Whether you’re planning your first dental practice straight out of Associateship, or launching your 10th in a growing group empire, designing and building a dental office is an extraordinary process - and at times both challenging and exacting.
This document outlines key steps, highlights dental office design project milestones, and provides significant detail on the development strategies and processes at Design Ergonomics (https://www.desergo.com).
Your dental office will have an enormous impact on your future; it’s where you’ll spend much of your time, determines your financial security, and allows you to bring health and well-being to the community.
Design Ergonomics would be honored to be part of your creation process.
Presentation for the IASA January 2016 eSummit on business-architecture - see http://iasaglobal.org/monthly-esummit/
Exploring the context of business-architecture: upwards to the big-picture, downwards to implementation, sideways to connections and qualities, and avoiding design-mistakes that take us backward to business-models that really don't work...
Fundamentally rethink how your building works in order to improve tenant service, cut operational costs, and become a world class competitor! This Presentation delivers essential tips for improving building processes to stay competitive in a buy and hold economy.
Presented by: Faraz Memon
What is Business Process Re-Engineering? Why is now the time to Re-Engineer your operations? How to find and locate operational areas to improve upon. The first steps to Re-Engineering your process & benchmarking. How to approach technology decisions & data migration. The best practices for Business Process Re-Engineering
Register to view presentation On-Demand:
http://be.buildingengines.com/Reg-Webinar-On-Demand-BusinessProcess-Reengineering.html
Translating Big Raw Data Into Small Actionable InformationAlan McSweeney
Any approach to Big Data needs to be based rigorously on business value. Big Data exists across the organisation’s operating landscape and not just for customers. Such data presents the potential for significant value that can enhance the way organisations do business and interact with external parties. There is a need for a realistic and achievable approach to translating Big Raw Data into Small Actionable Information.
Big Data is intrinsically linked to digital operations and associated digital transformation.
So ignore the issues of scope, lack of definition, conflicts, differences and complexity and focus on the identification, specification, development and implementation of approaches, strategies, processes, expertise, solutions and systems and data that can provide actionable information to achieve outcomes that produce business value.
The approach to generating real value needs to encompass:
1. Definition and understanding of Big Raw Data landscape including data sources, platforms, systems and applications parties, journeys and interactions
2. Identification and selection of high potential value use cases for implementation for selected parties
3. Definition of IT strategies, facilities, tools, techniques and resources to reduce the volume of Big Raw Data to translate it into Small Actionable Information
4. System and application changes to actualise use cases
5. Understanding and appreciation of wider operational context – Campaign Management, Customer Relationship Management, Customer Experience Management, Customer Value Management
6. Implementation of underpinning data governance and data privacy protocols
7. Organisational and process changes to identify, implement and operate use cases
There are only a limited number of actionable insights available from Big Raw Data. There are only a limited number of actions the organisation can reasonably take. It is important not to swamp the organisation with lots of irrelevant pseudo insights. It is important to prioritise the actions recommended from the derived insights.
Exploiting Big Raw Data to generate business value requires resources. This means management commitment and sponsorship.
Strategic Innovation - Tools and TechniquesCorporater
Learn how to execute strategic innovation in an organization using the available tools and techniques including the balanced scorecard.
You will see:
- > How strategic innovation can be addressed within the balanced scorecard methodology
- > How it can be executed with an integrated strategic planning and performance management system
To read the first part of this two-part series on "strategic innovation", please click here - http://bit.ly/2K4J63b
Acknowledgment:
Originally written by Dan Montgomery and Gail Stout Perry for the Whitepaper titled "STRATEGIC INNOVATION" published by Corporater. Read the exclusive whitepaper here - http://bit.ly/2JN94ra
(BPR) is basically rethinking and radically redesigning an organization's existing resources to achieve dramatic improvements in critical, contemporary measures of performance, such as cost, quality, service, and speed.
Market Volatility Considerations for Scale-up Stage Tech Companies in 2023 - ...Dave Litwiller
Leading tools to help prepare for and to navigate increasingly turbulent times for scale-up stage tech firms:
- Scenario planning
- Productivity enhancement drivers, particularly for knowledge-based work
- Instrumenting and monitoring revenue generation dynamics for signs of significant market and customer changes
- Individual, group, and institutional methods to increase the velocity of learning and adaptation, as well as distributed action
- Increasing awareness and sensitivity to changes in customer value proposition and adoption decision mechanics
Getting Good And Staying Good At (Out)SourcingAlan McSweeney
There is an increasing and continuing trend of organisations moving from in-house solution delivery to sourcing solutions externally. Organisations are divesting themselves of what they see as non-core functions. This is intended to improve operational efficiencies by using external suppliers’ perceived abilities to provide cost-effective, fit-for-purpose solutions quickly using the right technology. The responsibility and accountability for solution delivery and operation stills lies with the acquiring organisation. An organisation’s outsourcing zone of opportunity represents a challenge for both suppliers and for the acquisition function. Learn lessons from the experience of others to define exactly what you want of your outsourcing arrangement.
5 Step Playbook to Designing and Building the Dental Practice of Your DreamsDesign Ergonomics, Inc.
Whether you’re planning your first dental practice straight out of Associateship, or launching your 10th in a growing group empire, designing and building a dental office is an extraordinary process - and at times both challenging and exacting.
This document outlines key steps, highlights dental office design project milestones, and provides significant detail on the development strategies and processes at Design Ergonomics (https://www.desergo.com).
Your dental office will have an enormous impact on your future; it’s where you’ll spend much of your time, determines your financial security, and allows you to bring health and well-being to the community.
Design Ergonomics would be honored to be part of your creation process.
Presentation for the IASA January 2016 eSummit on business-architecture - see http://iasaglobal.org/monthly-esummit/
Exploring the context of business-architecture: upwards to the big-picture, downwards to implementation, sideways to connections and qualities, and avoiding design-mistakes that take us backward to business-models that really don't work...
Fundamentally rethink how your building works in order to improve tenant service, cut operational costs, and become a world class competitor! This Presentation delivers essential tips for improving building processes to stay competitive in a buy and hold economy.
Presented by: Faraz Memon
What is Business Process Re-Engineering? Why is now the time to Re-Engineer your operations? How to find and locate operational areas to improve upon. The first steps to Re-Engineering your process & benchmarking. How to approach technology decisions & data migration. The best practices for Business Process Re-Engineering
Register to view presentation On-Demand:
http://be.buildingengines.com/Reg-Webinar-On-Demand-BusinessProcess-Reengineering.html
Translating Big Raw Data Into Small Actionable InformationAlan McSweeney
Any approach to Big Data needs to be based rigorously on business value. Big Data exists across the organisation’s operating landscape and not just for customers. Such data presents the potential for significant value that can enhance the way organisations do business and interact with external parties. There is a need for a realistic and achievable approach to translating Big Raw Data into Small Actionable Information.
Big Data is intrinsically linked to digital operations and associated digital transformation.
So ignore the issues of scope, lack of definition, conflicts, differences and complexity and focus on the identification, specification, development and implementation of approaches, strategies, processes, expertise, solutions and systems and data that can provide actionable information to achieve outcomes that produce business value.
The approach to generating real value needs to encompass:
1. Definition and understanding of Big Raw Data landscape including data sources, platforms, systems and applications parties, journeys and interactions
2. Identification and selection of high potential value use cases for implementation for selected parties
3. Definition of IT strategies, facilities, tools, techniques and resources to reduce the volume of Big Raw Data to translate it into Small Actionable Information
4. System and application changes to actualise use cases
5. Understanding and appreciation of wider operational context – Campaign Management, Customer Relationship Management, Customer Experience Management, Customer Value Management
6. Implementation of underpinning data governance and data privacy protocols
7. Organisational and process changes to identify, implement and operate use cases
There are only a limited number of actionable insights available from Big Raw Data. There are only a limited number of actions the organisation can reasonably take. It is important not to swamp the organisation with lots of irrelevant pseudo insights. It is important to prioritise the actions recommended from the derived insights.
Exploiting Big Raw Data to generate business value requires resources. This means management commitment and sponsorship.
Strategic Innovation - Tools and TechniquesCorporater
Learn how to execute strategic innovation in an organization using the available tools and techniques including the balanced scorecard.
You will see:
- > How strategic innovation can be addressed within the balanced scorecard methodology
- > How it can be executed with an integrated strategic planning and performance management system
To read the first part of this two-part series on "strategic innovation", please click here - http://bit.ly/2K4J63b
Acknowledgment:
Originally written by Dan Montgomery and Gail Stout Perry for the Whitepaper titled "STRATEGIC INNOVATION" published by Corporater. Read the exclusive whitepaper here - http://bit.ly/2JN94ra
(BPR) is basically rethinking and radically redesigning an organization's existing resources to achieve dramatic improvements in critical, contemporary measures of performance, such as cost, quality, service, and speed.
Market Volatility Considerations for Scale-up Stage Tech Companies in 2023 - ...Dave Litwiller
Leading tools to help prepare for and to navigate increasingly turbulent times for scale-up stage tech firms:
- Scenario planning
- Productivity enhancement drivers, particularly for knowledge-based work
- Instrumenting and monitoring revenue generation dynamics for signs of significant market and customer changes
- Individual, group, and institutional methods to increase the velocity of learning and adaptation, as well as distributed action
- Increasing awareness and sensitivity to changes in customer value proposition and adoption decision mechanics
Technology challenge faced by consumer goods organisationsCarl McInerney
In this article I consider key technology challenges faced by consumer goods organisations, transformation project focus and what manufacturers should do to address the challenge.
The presentation is recycled from a piece of strategy work I recently conducted and I hope you find it of some value.
Making advanced analytics work for you.
Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data....
Integrating A.I. and Machine Learning with your Demand ForecastSteve Sager
There is a paradigm shift in the way companies forecast demand. Learn how you can leverage advanced machine learning to understand how business drivers outside your walls will impact enterprise data.
The big-data explosion is driving a shift away from gut-based decision making. Marketing, in particular, is feeling the pressure to embrace new data-driven customer intelligence capabilities.
Marketers working 70-80 hours a week is not a great thing to hear.
But the requirement for them to have such a large amount of work time causes problems in the data selection and filtering.
Hence many marketers flunk the big data test
this presentation pays attention to the to competitor analysis and how to conduct especially for an entrepreneur that's working on a shoe string budget.
[Project] FRAMEWORK FOR SUPPORTING “BUSINESS PROCESS REENGINEERING “-BASED BU...Biswadeep Ghosh Hazra
A short presentation on Business Process Re-engineering Based Models. It consists of Strategic, Project Management, Information Technology, Top Management and Cultural Factors. There are various models/frameworks and indicators like- Porters 5 Forces Model, 4 CSFs for BPR Implementation, From-to analysis, Financial Indicators.
Similar to Strategic Intelligence in Growth Stage Technology Businesses - Dave Litwiller - June 2018 (20)
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Dave Litwiller
In an expanding range of tech, AI, and advanced manufacturing industries, there are growing issues and concerns for assuring:
- Product safety and safety-related quality
- User/patient safety
- Employee/contractor safety
As well as the wellbeing of other stakeholders
Optimizing C-Suite Dynamics - Nov 2 2023 - Dave Litwiller - Public.pptxDave Litwiller
In this presentation, Dave Litwiller explores the critical aspects of optimizing C-Suite dynamics in scale-up stage technology companies. Collaborative leadership dynamics are vital in influencing a company's performance during rapid growth and evolving markets. The core model for the C-Suite, inspired by Peter Drucker, identifies the roles of Outside Visionary, Inside Visionary, and Disciplinarian. The CEO team construct is discussed, emphasizing its strengths in reducing CEO isolation and maintaining defined roles.
Key vital sign indicators for C-Suite teams are highlighted, focusing on decision-making and diversity of thought. The distinct challenges of the Disciplinarian role are addressed, including the need for a deep understanding of operational realities. The presentation also touches upon interpreting C-Suite criticisms and common friction areas among team members.
To resolve conflicts and enhance C-Suite cooperation, various mechanisms and strategies are explored, such as conflict resolution procedures, mediation, role changes, and alignment of goals and values. By understanding and addressing these dynamics, organizations can foster a more effective C-Suite.
Improving AI Development - Dave Litwiller - Jan 11 2022 - PublicDave Litwiller
A conversational tour through some things I’ve learned in helping scale-up stage client companies improve their AI development practices, especially where deep neural nets (DNNs) are in use.
Leading Transformation and Accelerating Change at Scale - Apr 20 2021 - Dave ...Dave Litwiller
In response to a burst of requests from the scale-up community for help working through the issues with larger magnitude change initiatives, here is a set of highlight thoughts and preferred approaches.
The Agile Learning Organization - Dave Litwiller - Sept 17 2020 - PublicDave Litwiller
Adapting Organizational Capabilities in Scale-up Technology Businesses to Thrive in the Strategic Environment using the Principles of TQM
- Enhance organizational learning capacity and agility
- Build connective capacity across functions and time horizons, to counter tendencies toward silos
- Develop leadership bandwidth at all levels to expand institutional capability for productive change
Future Office Layout and Productivity Considerations for Startups and Scale u...Dave Litwiller
The Covid-19 response which moved much office work to virtual has created a natural productivity experiment in the knowledge economy. The favourable early results being reported by firms with employees working from home are challenging the widespread assumptions about the merit of extremely open offices as were frequently adopted in technology companies prior to the pandemic. For companies that will continue to have offices which are now designing re-occupancy plans, social distancing requirements offer an opportunity to revert to potentially more productive forms of office layout.
Tata Group Dials Taiwan for Its Chipmaking Ambition in Gujarat’s DholeraAvirahi City Dholera
The Tata Group, a titan of Indian industry, is making waves with its advanced talks with Taiwanese chipmakers Powerchip Semiconductor Manufacturing Corporation (PSMC) and UMC Group. The goal? Establishing a cutting-edge semiconductor fabrication unit (fab) in Dholera, Gujarat. This isn’t just any project; it’s a potential game changer for India’s chipmaking aspirations and a boon for investors seeking promising residential projects in dholera sir.
Visit : https://www.avirahi.com/blog/tata-group-dials-taiwan-for-its-chipmaking-ambition-in-gujarats-dholera/
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
VAT Registration Outlined In UAE: Benefits and Requirementsuae taxgpt
Vat Registration is a legal obligation for businesses meeting the threshold requirement, helping companies avoid fines and ramifications. Contact now!
https://viralsocialtrends.com/vat-registration-outlined-in-uae/
Attending a job Interview for B1 and B2 Englsih learnersErika906060
It is a sample of an interview for a business english class for pre-intermediate and intermediate english students with emphasis on the speking ability.
Kseniya Leshchenko: Shared development support service model as the way to ma...Lviv Startup Club
Kseniya Leshchenko: Shared development support service model as the way to make small projects with small budgets profitable for the company (UA)
Kyiv PMDay 2024 Summer
Website – www.pmday.org
Youtube – https://www.youtube.com/startuplviv
FB – https://www.facebook.com/pmdayconference
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
Enterprise Excellence is Inclusive Excellence.pdfKaiNexus
Enterprise excellence and inclusive excellence are closely linked, and real-world challenges have shown that both are essential to the success of any organization. To achieve enterprise excellence, organizations must focus on improving their operations and processes while creating an inclusive environment that engages everyone. In this interactive session, the facilitator will highlight commonly established business practices and how they limit our ability to engage everyone every day. More importantly, though, participants will likely gain increased awareness of what we can do differently to maximize enterprise excellence through deliberate inclusion.
What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
RMD24 | Debunking the non-endemic revenue myth Marvin Vacquier Droop | First ...BBPMedia1
Marvin neemt je in deze presentatie mee in de voordelen van non-endemic advertising op retail media netwerken. Hij brengt ook de uitdagingen in beeld die de markt op dit moment heeft op het gebied van retail media voor niet-leveranciers.
Retail media wordt gezien als het nieuwe advertising-medium en ook mediabureaus richten massaal retail media-afdelingen op. Merken die niet in de betreffende winkel liggen staan ook nog niet in de rij om op de retail media netwerken te adverteren. Marvin belicht de uitdagingen die er zijn om echt aansluiting te vinden op die markt van non-endemic advertising.
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
2. INTRODUCTION
• A guided tour through the pivotal moments of my career in
growth stage technology enterprise general management
• A look at the context, necessity and contribution that
could be gained from detailed strategic intelligence in
those situations
3. OVERVIEW
• Motivations for Strategic Intelligence
• Primary Bases of Data Organization and Analysis
• Empirical Early Signaling Value – both of opportunity and threat
• Modeling Tools
• Leading Data Sources
- Break –
- Case Studies
- Getting Strategic Intelligence Right
- Warning Signs of Difficulties
- Sustaining Success: Eternal Challenges of Strategic Intelligence
6. WHY STRATEGIC
INTELLIGENCE?
WHY NOW?
• With time pressures and information overload, it has become easy to
insidiously filter our way to information and intellectual silos
• The people we associate with
• The electronic communication filters we apply
• The biases we bring, both conscious and unconscious
• The ideology, methods and short-cuts that worked for us in the past
• Without active offsetting measures, it is very easy to end up in an
echo chamber as time goes on
• The tendency toward a kind of echo chamber can be reinforced by
the drive to build a Cult of X kind of company
• Even if X in itself is not a malign thing
• Who wouldn’t want to build a company that can defy reality a bit,
stretching the boundaries of what should be possible?
7. MOTIVATIONS FOR
STRATEGIC
INTELLIGENCE
• Sort out fact from fiction about the competitive environment
• Ground objectivity about what constitutes best in class
performance versus good, average, or worse
• Triangulate on the most critical strategic inferences to inform
management decision making
• Increase amenity to making changes to get better, when
better is demonstrably possible in the competitive and
benchmark environment
• Provide counterweight to noisy anecdote-driven decision
influence (law of small numbers) and narrative fallacy
• See through bias, filtering and emotional short-cuts that
people might otherwise want to guide them
8. MOTIVATIONS FOR
STRATEGIC
INTELLIGENCE
• Balance the richness, but potential tunnel vision of data
coming from internal MISs, CRMs, development tools and
test equipment
• Counteract the tendency in disordered information
overload to primitively call the arguments on each side of
a debate a wash, and then make an overly emotional
decision
• Keep up in the rapid co-evolution with the environment, to
continue driving for a moving global optimum rather than
settling for a local peak
9. MOTIVATIONS FOR
STRATEGIC
INTELLIGENCE
• Core convictions:
• Informational advantages in the hands of those willing to
act on that advantage can confer a significant leg up in
strategic impact and financial return
• The hundreds of $millions or $billions of economic activity
in and around your sector external to your enterprise can
provide as much or more information as the most detailed
financial and management decision support analytics from
within
11. TRACKING BASIS
• Two primary strategic environment tracking methods:
• By competitor, potential competitor and industry participant
• By industry vertical (application sectors)
• Secondary matters are usually tracked subordinate to the
primary methods:
• Technology and technology convergence over time
• Operations
• Geographic and regulatory variations
• Reference class benchmarking (comparison class)
• Especially in emerging industries, where in-market, reliable
proof points are harder to come by
12. MARKET PARTICIPANT
TRACKING
For each entity of interest, usually a corporation:
• Time series of developments spanning corporate, product,
technology, operations, market, customer, distribution,
financing and staffing
• Similar tracking applies, be it for
• Competitors in a market
• Ecosystems players
• Distributors
• Suppliers
• Complementary product or service providers
16. FOUNDATION OF
STRATEGIC
INTELLIGENCE
• Read prolifically
• Keep detailed notes, including quality of data sources
• Differences over time are one of the most powerful way to reveal
trends and changes which reflect evolving marketplace and
competitor reality
• The goal is to fill in the puzzle, the journey is to enjoy filling in the
pieces
• There is much more in the public domain and near public domain
than people realize; this is not about violating confidences
• Diligence and consistency counts
• People who do this need to be good at making and testing
assumptions and interpolations
• It is like good journalism:
• Be intellectually engaged, but emotionally detached;
• Fallibilism dictates that the purveyor should never be 100% certain
17. BENCHMARKING
• If done right, strategic intelligence activities should
provide an evolving, quantitative model for benchmarking:
• R&D Productivity
• COGS
• Sales Productivity
• Market Share
• Relative and Absolute Growth
• Overall Management Effectiveness
• Financing and Acquisition Valuation
• Make vs. Buy for Incremental and Transformative
Advances
18. BENCHMARKING
Qualitative Benefits (in the early market for a new tech):
• Identification if the company is getting to true KOLs, or is working
with B-list wannabes
• Determining the weightings in the relationship between
technology, manufacturing/operations and distribution to
sustainably win in the market
• Knowing what price-performance thresholds and adoption cues
signal the likely arrival to stay of disruptive new technology vs. the
head fakes of many would be challengers
• Helping the company’s executive and board of directors to guide
and evolve strategy in step with competitive reality
• Identifying the most efficacious ideas and techniques from
competitive, adjacent, and analogous reference class companies
for adapted incorporation in the company’s continual evolution
19. REFERENCE CLASS
FORECASTING
a.k.a. Comparison Class Forecasting
• Method for predicting the future based on analogous past
situations
• Counters human bias toward overconfidence and
statistical misrepresentation of past circumstances
• Provides an outside-in perspective on new initiatives,
including the development and marketing of new
technology, rather than an inside-out view of traditional
business planning
“By supplementing traditional forecasting processes, which tend to focus on a
company’s own capabilities, experiences, and expectations, with a simple
statistical analysis of analogous efforts completed earlier, executives can
gain a much more accurate understanding of a project’s likely outcome.”
Source: Lovallo & Kahneman, HBR, July 2003
21. PICKING INSTRUCTIVE
ANALOGS AND ANTI-LOGS IN
REFERENCE CLASSES
• Availability bias issue – People are easily drawn to the most recent or best
understood example, rather than the most instructive
• Meta examples to broaden perspective:
• Agriculture
• Metals and materials
• Petrochemicals
• Electrification and electricity generation
• Biotechnology and pharmaceuticals; medtech
• Automotive
• Aviation and aerospace
• Wireline and fiber optic communication
• Broadcast
• Wireless communication
• Semiconductors – lithography driven vs. analog, RF & MEMS
• Computing – mainframe, mini, PC, mobile/smart phones, IoT,…
• Analytical instruments
• Software, data science and artificial intelligence
• Internet
• Robotics
22. APPLICATION
MARKET PROFILING
Main Issues to Track and Model:
• Size, growth rate, value of success, cost of failure
• Incumbent solutions
• Major accounts, distribution channels, service providers
• Unit economics, especially from early deployments
• Emergent complexities
23. APPLICATION
MARKET PROFILING
Adoption-Rejection Behaviour:
• Reflects RoI & payback time, perceived risk, integration to
existing workflow & tools, social innovation diffusion factors
Source: Zvi Grilliches, Hybrid Corn and the Economics of Innovation, Science, 1960
27. EARLY WARNING POTENTIAL
OF STRATEGIC
INTELLIGENCE
• Market participant
• Even with private companies, suitable strategic intelligence often can
achieve advance warning of significant business up- or downturns 3
to 6 months in advance of more overt signals
• Market sector
• Often can identify use case and business case strength and short-
term unresolvable issues 1 to 2 years in advance of a more settled
consensus being reached
• Industry character
• More accurate sense of analog and anti-log examples of past
technology industries from which to draw modeling inferences, as
much as several years in advance of the wider opinion
• Counter availability bias which can otherwise overly drive assumptions
28. INDUCTIVE AND
DEDUCTIVE VALUE
• Time-based profiles of market participants, industry
sectors and related technology and distribution trends
• Identification of drivers, context and transpositions to
achieve higher productivity, performance and impact in
your enterprise
29. MODELING TOOLS
• Steady State Market Share:
• Non-networked: #1, 40%; #2, 25%, #3, 10%-15%
• Strong network effects: #1, 90%; #2, 9%; #3, 0.9%
• => Relation to economies of scale in R&D, Operations
• Profit Pool:
• ~85% of the profit pool in an industry usually goes to the
top ~75% market share
30. MODELING TOOLS
• Product and business line extension adjacency
relationship to success rate
• Adjacency by: technology, operations, and distribution
32. MODELING TOOLS
• It requires $1.50 of total investment to gain $1.00 of annual
market share with mediocre technology in a crowded
market
• Significantly better revenue gains require better
technology, superior go-to-market, and greater influence
over the development of the marketplace
33. MODELING TOOLS
• Payroll cash costs (salary, benefits, payroll taxes) will
represent ~50% of all cash expenses in a software business,
and somewhat less in a hardware business
• As the largest single cost load, headcount over time is the
most difficult measure of performance to deceive
• Fundraising success, a sweetheart large deal or short-term
high margins can allow unsustainably high headcount for a
while
• But, eventually staffing has to come into line with the
revenues, margins and cash flow the business generates
• The total cost of having an individual contributor employee,
including benefits, infrastructure, supervision, etc. is about
3* what the employee is directly paid
• Si-V payroll costs are about 2* those of KW
34. MODELING TOOLS
• Technology Adoption Curve – Everett Rogers
• Head fake potential for insurgent technologies drops
significantly once the early majority enters
• Technology, product and distribution strategy changes
considerably after early majority onset
• Early market share, R&D productivity and API/interoperability
strategy-execution are critical to get the big ride on the wave
35. MODELING TOOLS
• S-Curves (adoption, growth) are smooth in aggregate, but
much more discrete in practice when carefully analyzed
Source:
Unrelenting Innovation,
by Gerard Tellis,
Jossey-Bass
36. MODELING TOOLS
• Precedent and adjacent market adoption pattern
characteristics often have significant predictive value,
especially for the time dimension, because of how
powerful social factors are in the adoption of innovation
• Rise Time: Time from launch to achieve 20%, 50% and
80% penetration
• Time for leading vendor to achieve $X million in annual
sales
• Careful: When did the project really start, vs. when do
executives retroactively report that it started
• Degree of product commonality and product diversification,
and the related technological, manufacturing and
applications engineering distance between the main use
cases
37. MODELING TOOLS
• Power Law:
• First order: 80/20; averages don’t tell much (vs. Gaussian dist’n)
• Second order: 95/5 <- Becoming more common??
• Resources and knowledge pool and co-evolve
• Difference between perception and reality
• Revenue, profit, valuation, distribution power, etc.
• Inference: Winner, keep new categories from emerging
Challenger: Innovate to create new categories
38. MODELING TOOLS
• Fermi Estimates
• Make justified estimates about quantities, including mins
and maxes of many constituent terms
• With fine grained estimation of individual contributing
items, assumptions and biases become clear
• With fine grained estimation, errors of individual items tend
to cancel provide order of magnitude accurate results
41. MODELING TOOLS
• Comparative longitudinal studies (over time)
• Often reveal insights about competitors and reference class
companies far better than isolated profiles, limited time series,
or vivid recollections
• Best: If comparisons can be done through recent similar time
windows, when comparable participants were operating with
similar technology, distribution, social and economic forces
• Best: Similarity of entrepreneurial drive, resources and
limitations of study group of businesses
• This is a common methodology in business research and
cultural anthropology
• Most Important: Watch what competitors and reference class
companies do, not what they say they’ll do, except to
compare their ability over time to set a forecast and hit it
42. OTHER GO-TO
CHARACTERISTICS
• Most progress comes from the ability to do many small
mutations fast
• Applies to technology, product, organization, distribution,
supply chain, and issue resolution
• Speed responding to the little problems that arise portends
much about the ability to do bigger things well
43. OTHER GO-TO
CHARACTERISTICS
• There is usually a dominant time constant in technology
adoption
• Understand what it is, why it is, and thus how to read the
forward analytics with greatest accuracy
• Informs the interventions that will be most productive to
accelerate adoption
• The issues are often as much social as technical
44. OTHER GO-TO
CHARACTERISTICS
• Profit usually pools disproportionately in parts of the
market web. One example: Smile Curve
• Note: the profit pool vs. market chain is often not smooth
and not monotonic (even in the second derivative)
45. OTHER GO-TO
CHARACTERISTICS
Accounts Receivable and Inventory:
• If reliable financial data over time is available
• Such as from publicly listed entities of interest, or,
• Private companies in jurisdictions where financial statements
have to be publicly disclosed
• Then, changes normalized to sales revenue in:
• Accounts Receivable (A/R), and,
• Inventory, including the ratios between raw materials, work-in-
progress, and finished goods
Often have very high value about the health trend lines of the
profitability of a company under study
46. IF YOU’RE REALLY IN A
PINCH FOR A
PREDICTIVE MODEL
Rene Girard:
• Most of human behavior
is based upon imitation,
rival and differentiating
Charlie Munger:
(Warren Buffett’s partner)
47. LEADING PUBLIC
DATA SOURCES
Google searches are, at best, only a starting point (ditto for
Baidu). Much is not well indexed. Similar for Wikipedia.
Where to go for better public and near-public data?
• News, especially local news, particularly local language from
responsible outlets and journalists
• Financial and securities disclosures, both of subject
companies and partners, especially analyst day, capital
market conference presentations and acquisition filings
• Podcast and Youtube interviews, where people tend to be
less guarded than in print
• Trade show bloggers, tweeters and photographers
• Aspiring industry mavens who leave a lot of on-line residue
and get out to most or all of the main events
48. LEADING PUBLIC
DATA SOURCES
• Corporate profile “leaks” to the business press
• Often done by retained i-banks to cultivate acquisition interest
• Patent filings laid open, primarily US and home country
• Government research grant applications
• Regulatory filings (such as FCC)
• Court filed litigation documents
• Banker’s books and corporate venture investment
solicitations
• Technical conference presentations (both positive- and
negative-space inferences)
• Suppliers and channel partners (subject to de-biasing their
self-interested spin)
49. PRODUCT
BENCHMARKING
• The limits of vendor documentation:
• Hardware: Specifications, term definitions, test methods, test
equipment and results interpretations can vary greatly among
competing vendors, and hide as much information as they reveal
• Software: Many vendors claim similar high level capabilities, but only
when you drill down do the usually significant differences in capability
and usability fully emerge
• Relying on published competitive specifications or lone user
impressions are dangerous as the main inputs for significant
decisions
• Benchmarking performance of competitive products is best done in-
house where consistency of test conditions can be achieved
• Next best is using a 3rd party lab
• Usually the best tracking method is the trajectory over time for each
performance attribute that users find valuable
51. CASE STUDIES
• Digital Image Sensors, Cameras and Semiconductors
(’97-’08)
• Technology and Application Sector Focus Choices in
Fragmented, Rapidly Changing Digital Imaging Markets
• Turnaround of Medical and Biotech Imaging Business Unit
• Fix, Sell or Shut: Digital Cinematography Business Unit
• Major New Growth Wave or Head Fake for Industrial
Machine Vision: Smart Cameras
• MEMS Foundry Services
52. CASE STUDIES
• Enterprise Software – Customer Communication Mgmt
(’08-’11)
• Lead, Follow or Get Out of the Way
• Drones (’11-’17)
• Agriculture
• Law enforcement
• DJI – what can be learned about a private company with
work
53. MACHINE VISION IMAGE
SENSORS AND CAMERAS
• Circa 1997, a local tech company had grown its image
sensor and digital camera business predominantly in
document scanning and postal sorting to ~$30M in sales
• The company was becoming a big fish in a finite sized
pond based on those beachhead applications
• It needed to continue to generate strong growth, having
gone public in 1996
• The company had toeholds in a number of additional
markets, through early adopter cross-over uses of its
standard (catalog) products, and custom developed
products
• The overall market for machine vision sensors and
cameras was large, but very amorphous in product
requirements across many sectors
54. MACHINE VISION IMAGE
SENSORS AND CAMERAS
• The main questions to answer at the time:
• What candidate market verticals to target next?
• To get to that answer, needed to understand for each
vertical:
• Size, growth rate, and system level technical trends
• Competitors and competitive intensity
• Leverage and gaps in current technology capability
• Extensibility of current operations and distribution
• Studied ~70 discernable application sectors
• Everything from Astronomy to various X-Ray Imaging uses
55. MACHINE VISION IMAGE
SENSORS AND CAMERAS
• Desirable sweet spot for growth:
• Markets large enough to fuel significant growth for years to
come, but not so large as to take on behemoth competitors
the company couldn’t handle
• Verticals requiring technology and operational capability
packages where the company’s existing assets were
already 80% to 90% complete
• Bound risk and time to success, especially when requiring
financially material investments in a public company
setting
56. MACHINE VISION IMAGE
SENSORS AND CAMERAS
• Added challenge:
• As an OEM component provider, the time from product
concept through development and release, and then
system customer design-in through release and ramp
could take 3 to 5 years in total
• Technology and market forecasting had to be sound, both
for direction and magnitude
• Sunk cost investments to go after major new applications
and technologies were significant
57. MACHINE VISION IMAGE
SENSORS AND CAMERAS
• Diversity of applications, technology requirements,
markets
Source: RIA/AIA 2008 Machine Vision Mkt. Study
58. MACHINE VISION IMAGE
SENSORS AND CAMERAS
Example Outcome: Semiconductor wafer, mask and reticle inspection
KLA-Tencor
Hitachi
Applied
Materials
Rudolph
Technologies
Nanometrics
Veeco
Therma-
Wave
ADE
Leica
Bio Rad Other
Inspection & Metrology
Fractal-like market concentration and technical diversity in the sector, much as
the larger machine vision industry
59. MEDICAL AND BIOTECH
IMAGING SYSTEMS
Setting:
• The company had traditionally not been a strong vendor
of imaging technology for ionizing radiation imaging, and
slow-scan, high dynamic range sensors and cameras
• This sector was poised to grow significantly in the years
to come, at or above the rate of the company’s traditional
industrial machine vision markets
• To fill this gap, in the early 2000’s the company acquired
an early stage developer and manufacturer of x-ray
imaging sensors and cameras in the US
60. MEDICAL AND BIOTECH
IMAGING SYSTEMS
• After a few years, the acquired business was struggling for growth
• CRM analytics and management regularly suggested an upswing
was near, but the horizon kept receding as time rolled forward
• Issue: The misunderstanding of the real rate of progress of internal
account development was mirrored by misunderstanding of the
external environment
• Hopeful optimism for a quick rebound at the onset of difficulty had
institutionalized and amplified into a number of specious beliefs and
dogmas about the internal and external situation
• Action: Bottom-up external re-evaluation of the key target markets,
and major prospects in each sector
• Separate fact from fiction to get a reliable handle on attainable
growth, desirable target accounts, and near-term levers for an
operating-level turnaround of the business
61. MEDICAL AND BIOTECH
IMAGING SYSTEMS
• Findings
• Three major customers the business relied upon for its near
term vitality
• Digital Mammography: In financial and regulatory difficulty,
declining market share it its end market, and unclear ability to
afford to stay competitive through next generation R&D of its
system product
• Protein Crystallography: Substantially cash cowing the
product line in which it used the company’s sensors, and
would not significantly reinvest to get more competitive
• Small Animal CT: The customer was healthy, but small, and its
growth alone could not reflate the business as it was
• Action: Expedited next generation product development of a
broadly applicable CMOS x-ray sensor and camera
62. DIGITAL
CINEMATOGRAPHY
• Time Period: 2000 – 2008
• Era: Advent of digital cinema photography camera usage in principal
photography of movies, episodic TV and big budget commercials
• Issues:
• Ability for 4K digital image capture to supplant film, on aesthetic and
technical grounds
• Adoption speed proclivities in project-based film industry
• CMOS vs. CCD image capture
• Disruptive potential or head-fake of $30K ASP insurgent camera system
price from a new vendor vs. deemed $300K-$400K legacy mechanical
film camera price and targeted CCD camera price
• Finite size of global market and profit pool relative to the inexorably rising
cost of up-front product and market development
• Little revenue or total production cost leverage from using digital cameras
vs. film
• Rate of likely obsolescence of digital cinematography cameras vs. legacy
mechanical film cameras, and business model implications for ecosystem
63. DIGITAL
CINEMATOGRAPHY
Key Decision Inputs:
• Market penetration of digital cameras, and penetration rate vs. previous digital
production and post-production technologies
• Early adopter to mainstream tipping point
• Market share
• Use by the most respected of the priesthood of directors of photography
• Separating real from would-be key opinion leaders (KOLs)
• Relative and absolute penetration of digital cameras by:
• Legacy mechanical film camera producers
• Cross-purposed high end broadcast cameras
• Up-performance DSLR cameras
• Insurgents pursuing low cost, high performance accessible to most at the price of a
legacy camera rental, for the benefit of ownership
• Market size, profit pool, growth rate, and implications for required market share to
return cost of growing capital investment
• Positive and negative externalities in movie production costs from the advent of
digital image capture during principal photography
• High statistical fall-out of movie projects going from concept to green-lit status
64. DIGITAL
CINEMATOGRAPHY
Social and Structural Issues:
• Lateral nature of Hollywood (rather than vertical integration) making it
harder to get everyone on the same page for changes that cross
organizational boundaries
• Maturity of the industry, meaning much spending power and
management time among major players are dedicated to similar
problems
• Oligopoly of the major studios, dampening competitive intensity to try to
get ahead with new technologies, and,
• Project-based nature of content creation
• Teams re-form from project to project, changing stakeholders
• Decision team reconstitution brings “solidarity of three” problem in risk
assessment about carrying innovations from past projects to new ones
(single missionary advocate for a risky position faces several opposers)
• Also, project-based work with team reform each project means IP moves
around, lessening the incentive for businesses to invest in differentiating
technological or work-process IP beyond a minimum competitive
threshold
65. DIGITAL
CINEMATOGRAPHY
Adoption timescale benchmarking example
(predecessor, competitor and adjacent techs):
Red - Major Release Lensing
HD - Episodic TV Digital HD Camera Use in US, English
Year Share
Year Years
Since
Launch
Event Share of US Episodic
TV Capture
2007 2.50%
2008 7% to 14% HD - 2/3" Major Release Lensing
1999 0 Introduction 0.0%
2000 1 Launch 0.0% Genesis - Major Release Movie Cinema Photography Lensing
Year Share of Major Release
Principal Photography
2001 2 Experiments, Commercials 0.0% Viper, F900/950, Varicam
2002 3 0.0%
Year Years
Since
Launch
Event Share of Major Release
Principal Photography
Number
of
Cameras 2002 0.5%
2003 4 First HD Series 2.0% 2003 0.5%
2004 5 11.0% 2004 0 Introduction 0.0% 2004 1.0%
2005 6 20.0% 2005 1 Launch 2.5% 12 2005 2.0%
2006 7 31.5% 2006 2 8.5% 50 2006 7.0%
2007 8 40% 2007 3 11.5% 90
Avid Film Composer Digital Editing Suite - Partial Editing Avid Film Composer - Full Editing, Feature Length Movies 3-D - Major Release Production
Year Years
Since
Launch
Event Market Share Year Years
Since
Launch
Event Market Share
1992 0 Launch 0.0% 1992 0 Launch 0.0% 2005 0.5%
1993 1 First Movie 0.2% 1993 1 2006 1.0%
1994 2 Two Movies 0.5% 1994 2 2007 2.0%
1995 3 Dozens of Movies 5.0% 1995 3 2008 5.0%
1996 4 10.0% 1996 4 2009 7.5%
1997 5 20.0% 1997 5 5.0% 2010 10.0%
1998 6 50.0% 1998 6 2011 12.5%
1999 7 60.0% 1999 7
2000 8 65.0% 2000 8
2001 9 70.0% 2001 9 12.5%
2002 10 75.0% 2002 10
2003 11 80.0% 2003 11
2004 12 85.0% 2004 12
2005 13 87.5% 2005 13
2006 14 90.0% 2006 14 60.0%
Full Digital Intermediate in Wide Release Hollywood ProductionsFull Digital Intermediate in India (Bollywood) Productions 4K Digital Intermediate in Wide Release Hollywood Productions
Year Years
Since
Launch
Event Market Share Year Years
Since
Launch
Event Market Share Year Market Share
1993 0 Commercials 0.0% 1993 0
1994 1 Music Videos 0.0% 1994 1
1995 2 0.0% 1995 2
1996 3 0.0% 1996 3
1997 4 0.0% 1997 4
1998 5 0.0% 1998 5
1999 6 0.0% 1999 6
2000 7 First wide release 0.0% 2000 7
2001 8 0.3% 2001 8
2002 9 7.0% 2002 9 Introduction
2003 10 19.0% 2003 10 0.2%
2004 11 32.0% 2004 11 2.0% 2004 0.5%
2005 12 50.0% 2005 12 6.0% 2005 1%
2006 13 66.0% 2006 13 15.0% 2006 5%
2007 8%
2008 10%
66. DIGITAL
CINEMATOGRAPHY
Adoption timescale example inferences:
• 10% of ultimate market share can happen 3-5 years after launch of working product
• 50% of ultimate share takes 6-9 years for partial use of a systemic new technology,
and a 10-15 years for use that totally displaces the incumbent
• Order of magnitude cost reduction is the standard for driving faster adoption within
these ranges
• Sustained high growth rates come from being associated with distinctive audience
experiences in the highest grossing projects (herd dynamics)
• 50%-80% share of market is ultimately possible with exceptional performance and
execution
• Point technologies (incremental) in production workflows move much faster (2* to
4*) than those requiring systemic change
• 4K (next generation tech) lags 2K (current generation tech) by about 5 years
• The incremental benefits of 4K in DI are much less vs. 2K, than 2K was relative to
the incumbent technique DI replaced. 4K DI is being adopted at roughly half the
pace of 2K DI.
67. DIGITAL
CINEMATOGRAPHY
Bottom Line Near-Term Indications for Action:
• Show revenue enhancement for customers from early projects
using tech (or at least significant cost savings)
• Show how all players felt early projects were de-risked or
creative control was enhanced from using the tech
• Show learning curve for getting superior results from the new
tech to be << one project
Longer-Term Indications:
• Stop-loss threshold, should operating improvement not
materialize
68. DIGITAL
CINEMATOGRAPHY
Epilogue
• By 2006:
• R&D productivity was competitively, objectively sub-par;
technology and manufacturing leverage were proving elusive
• Real KOLs were adopting competitive digital camera
products, for mainstream wide-release movies, episodic TV,
and high profile commercials
• Order of magnitude lower price digital CMOS imager cameras
were at an advanced state of development, pending release
• Success of adjacent DSLR CMOS cameras (Canon D30 and
later models from multiple vendors) since 2000 indicated
advent of CMOS was probable
• Adoption of alternate digital cameras (relative to typical 15%
tipping point threshold)
• TV and commercials – 31%
• Wide release movies – 9% - arguably, still up for grabs
69. DIGITAL
CINEMATOGRAPHY
Epilogue
• By 2007:
• Adoption of alternate digital cameras in principal photography
• TV and commercials – 40%
• Wide release movies – 14%
• Price busting 35mm CMOS imager digital camera launched
by Red Digital Cinema
• 2008:
• The company persisted and continued to press ahead
• Successful activist shareholder intervention to revamp board
of directors and reform strategy
• Digital cinematography business shut down
• Over $60M went into this venture since its inception
70. MEMS FOUNDRY
SERVICES
Time: 2002-2008
Issues:
• Acquired semiconductor foundry to secure access to production for
specialized image sensor fabrication
• Captive image sensor production though was too small to consume
enough of the foundry capacity to be viable (<20% of output)
• Needed to avoid lithography and wafer size based competition
• Most promising growth market matched to equipment and process
capabilities: Micro-Electro Mechanical Structures (MEMS)
• Application and customer focus
• Context: history of “MEMS Death Spiral” for multi-customer foundry
services, where new equipment, materials and processes had to be
added faster than the rate of sustained revenues, margins and cash
flow
72. MEMS FOUNDRY
SERVICES
• Decisive Issues to Profile about Competitive Environment
• Threshold of R&D and CapEx to be sustainable, adjusted for
technology node, process mix and product diversity
• Strategic intelligence impact
• Clear dichotomy of profitability and sustainability based on scale
• Objective sense of the time to conceive, develop and achieve volume
production of entirely new processes and devices
• Outcome strategy drivers
• Process transfer for small volume work, sidestepping much of the
R&D and CapEx
• Work with a portfolio of large potential volume emerging
opportunities, with bounded material and process limits matched to
current capabilities
73. SMART CAMERAS
Time: 1997-2008
Era:
• Advent of low cost machine vision appliances
• Integrating camera, frame grabber, image processing
software
• Small, low cost package
• To access heavier industry, consumer packaging, and
pharma/med device sectors where more expensive, larger,
and complex to deploy machine vision had previously tried
and struggled to gain traction
74. SMART CAMERAS
Issues about which confusion was complicating management decision
making:
• Supplier market share and fragmentation
• Fuzziness in the perceptions after the top 2 or 3 players
• Relative leverage of technology vs. distribution vs. customer service
• Real rate of penetration (market adoption-rejection behavior), and
attainable rate of change
• Unit deployment economics and business model w/ less tech’l users
• Use of income statement geography and selective memory loss to
make some vendors appear to be performing much better than they
really were
• Hangover effect from 2000-2003 tech bust when some of the
traditional markets for industrial machine vision were declared dead
and not coming back
• The industry was trying to will into existence a new savior product
category and market
75. SMART CAMERAS
Clouding issues further:
• Cult of Dr. Bob issue
• Widespread industry envy of the leading North American
player’s public awareness, valuation and bravado
Source: Cognex
Annual Reports
77. SMART CAMERAS
Basis of Research and Analysis
• Research to build rapid comparative profiles for all market
participants
• Half a page each, covering:
• Participant size and growth rate, and years since inception
• Relative prevalence in value prop and differentiation of
technology vs. distribution vs. operational prowess
• Financial performance and market performance
• Model and assets for each of distribution, operations and
R&D
• Analysis:
• Pair-wise comparisons among the market participant profiles
to reveal the correlations, anti-correlations and likely causality
that led to the strongest vs. average vs. worse outcomes
78. SMART CAMERAS
Key Strategic Intelligence Outputs to Drive Management Decisions:
• Accurate baseline market share and trends
• Thresholds of competitive efficiency in R&D
• Relationship between product diversity, distributor diversity and size
of customer base
• Pragmatic leverage assessment of existing distribution assets
• Ramp-up time and availability of new distributors
• Ability to set a forecast one to three years out, and largely hit it
• Cash Curve: Time to breakeven and payback time
• A more characterized and quantified estimate of the opportunity
available from continuing to invest in smart cameras (small market
share line of business) vs. other business units with more
significant market shares
79. CUSTOMER
COMMUNICATION
MANAGEMENT
Key Issue: Does the market want what we’re selling?
Prime Frame of Reference: Recent predecessor, competitor
and adjacent product vendor success trajectory
0
10
20
30
40
50
60
1 2 3 4 5 6 7
Revenue(US$MM)
Years Since Inception
Reference Company Growth Trajectory
Aprimo
Document Sciences
Eloqua
Exstream
InSystems
StreamServe
ThunderHead
Unica
XMPie
80. CUSTOMER
COMMUNICATION
MANAGEMENT
Sometimes, you get lucky:
• Private company in the space, but HQ’d in the UK
• UK companies have to file financials in the near-public
• Some like to show off a bit (for future partners and
potential acquirers?)
81. CUSTOMER
COMMUNICATION
MANAGEMENT
Challenges:
• 2008-’10 financial crisis in full swing
• Cult of X issue around a pre-crisis sale of sector participant
Exstream Software to HP (since divested and acquired by
OpenText)
• Frame of reference moving what had been a professional
services business to a more scalable technology business
Inferences:
• Various insights about product, technology and go-to-market
tune-ups to reposition business to a sustainable trajectory
82. DRONES IN AG
The Knowable, Likely Head Fake of Precision
Agriculture
• The False Hope to Become a Big Market for Surveying Drones
83. DRONES IN AG
• 2013: Initial breathtaking projections (US example)
Source: AUVSI Economic Report,
2013
• Careful analysis:
• Specious extrapolations from pesticide application drones in
Japan
• Assumption and reliance on system-level capability to exploit
high temporal and spatial accuracy crop data from drones
84. DRONES IN AG
• 2013: Research to make one question a little more deeply
• Slow precedent adoption rate and low ASPs of of GPS-
enabled precision ag technologies in the US
• Widespread adoption achieved only when ASPs of precision
ag techs dropped below $20K, and in some cases, under $2K
85. DRONES IN AG
• 2014: Empirical evidence of unexpected application
complexity and hidden costs
• Crop varieties -> Substantive technical differences to
activate value from drone imaging
• Conservative, cost conscious farmers
• Complexity of flying drones and post-processing data to
generate actionable insights
• Challenges of acting on those insights with existing crop
input application technologies
• Opportunity cost vs. alternative yield-cost enhancing
potentials
86. DRONES IN AG
• 2014-2015: Gold rush of services providers
• Effort to make the technology and workflow more
approachable to end farmers
• But, under observation, in less subsidized markets, anemic
service provider growth rates when studied over short- and
medium-term
87. DRONES IN AG
• 2015-2015: Sober experience of those having used drones in
ag for several years
• Jurisdictions with earlier regulatory relaxation for commercial
use of drones, such as Brazil and France
• Yield impact and RoI are marginal, not fundamental
• Realization that it takes multiple years to fully evaluate the
impact of any new precision ag technology, given the
variability of weather factors
• Attribution difficulties
• Precipitous price drops to try to get traction, not just for the
drones but for the payloads too
88. DRONES IN AG
• 2015-2016: Elevated churn rates of early adopters farmers
using SaaS for crop management drone analytics
• Primary strategic emphasis of many SaaS image analytics
company shift to insurance, mining, surveying and
construction
• Viable agricultural applications in the early market limited
to high value crops such as viticulture and almonds
• Other factors: Growing competition from higher resolution
satellites and microsatellites with more frequent passes
and denser coverage
89. DRONES IN AG
• 2017: Capitulation
• “Encouraging farmers to adopt drones also proved harder
than expected,” notes Chris Anderson of 3D Robotics. “The
agricultural use of drones sounds good in theory—feed the
world, save the planet—but is difficult in practice. The market
is very fragmented and conservative, with many subsidies
and distortions, and some of the social goods that flow from
using drones, such as reducing run-off of chemicals, do not
benefit farmers directly.”
• The agricultural market “is littered with struggling technology
companies that have tried to break in, says Jonathan Downey
of Airware.
• “What good are unmanned aircraft systems for agricultural
remote sensing and precision agriculture?” - USDA
90. DRONES IN LAW
ENFORCEMENT
• Reference class law enforcement analysis:
• Surveillance cameras
• Body cameras
• Digital imaging SaaS and video evidence admissibility
• License plate camera readers
• Encrypted radios
• Police helicopters and imaging payloads
• Night vision and thermal imaging systems
91. DRONES IN LAW
ENFORCEMENT
• The power of social media to track market penetration,
growth, and share by both units and $’s very closely
77%
12%
3%
3% 1%
1%
1%
1% 1% 1%
Announced or Completed US Law
Enforcement sUAS Deployments from Jan
1 to Dec 15 2016, N=138
DJI Manufacturer not Disclosed
Competitor A Competitor B
Competitor C Competitor D
Competitor E Competitor F
Competitor G Competitor H
92. DRONES IN POWER
GENERATION, T & D
INSPECTION
Unit Economics:
• Industry Consortia: Often can only agree to work on near-
term, shared challenges (to protect IP), and frequently
publish extensively, including on unit economics
93. DRONES - DJI
“The harder I work, the luckier I get.” – Samuel Goldwyn
500
2,700
200
150
250
DJI 2017(F) Sales by Product Line, US$ Million, made in mid-2016
Mavic Pro Phantom Inspire Matrice Other
Mavic and
Phantom Sales –
Multiple company
executives in
Chinese language
interviews
Inspire – Promotion
from 20,000th unit
sold during retail
store opening in
Hong Kong
Higher end
systems based on
extrapolation of US
FAA commercial
registry relative to
Inspire
Triangulation -
Amazon and
Alibaba sales
statistics
Actual DJI 2017 sales: US$2.9B
94. DRONES - DJI
• Forecasting:
• Watch headcount
• Other measures of corporate development are more easily
deceived
• Even headcount needs to be watched carefully; there’s a lot
of out of date information in circulation
Wikipedia, downloaded June 7/’18:
DJI, Aug. ’17:
• “DJI now has over 11,000 staff worldwide..” – Frank Wang,
Founder
96. GETTING STRATEGIC
INTELLIGENCE RIGHT
• There’s sometimes remarkably little support for what is
generally accepted wisdom
• Careful research and analysis over time reveals deeper, more
reliable facts
• Many people in an ecosystem want to create an aura of being
insiders, often trading to build personal credibility on what
they would like to believe or portray is privileged information
• Instead, what they emit is often just gossip of unconfirmed
veracity, but attention-getting specificity, or lightly reheated
public information
• Detailed strategic intelligence sorts the contenders from the
pretenders among sources and supposed facts with the ability
to corroborate the likely and certain and separate out the
unlikely and uncertain
97. GETTING STRATEGIC
INTELLIGENCE RIGHT
• Knowing what information is missing, which would be
most valuable to know, allows the most incisive, least
damaging, and likely to succeed information exchanges
when they need to occur with others in the industry
• When potentially significant new information comes to
light, its likelihood of being true can be quickly
ascertained based on other information already
marshalled, to allow the correct vector of response
98. GETTING STRATEGIC
INTELLIGENCE RIGHT
• Brains are not the problem in growth stage tech
• More difficult to manage are: Assumptions, ambition, frame
of reference/context, the relative merit of various analogs
and anti-logs, clique dynamics, ideological filtering, and
biases to justify past decisions and positions
• Can-do people, in can-do companies, in can-do industries
• Competitive drive can become neurotic
• People can act in know-ably flawed or unduly risky ways,
just to take action quickly with the tools they have
• Counter: Institutionalize thinking fast and slow
• Counter: At least a few people with broad awareness,
across the industry, adjacent industries, and over time
99. TACTICAL CHALLENGES
TO STRATEGIC
INTELLIGENCE SYSTEMS
Those opposed to the trends and likelihoods indicated, on
the grounds of bias or time pressures:
• Visionary:
• Interest may only last until the next shiny bright object
appears
• GSD Operator:
• Often wants to revert to whatever is tactically quickest, to
get the most to-do list items checked off fast
• Process Oriented Team Member:
• The changes in organizational priority and behaviors
implied can be anathema to the desire for an ordered,
predictable routine
100. WARNING SIGNS
• Uncomfortable inferences for change are nervously
acknowledged or superficially refuted based on little
contrary evidence, and then things stay the way they were
before
• The rate of change inside the company is significantly
outpaced by the competitive environment
• The company’s bureaucracy resists or factionalizes
necessary shifts
• There’s more loyalty to functions, department heads and
key people than to the overall performance of the
business
101. WARNING SIGNS
• Greater value is placed on executing the current strategy
with declining productivity than on finding a new strategy
• The bandwidth dedicated to many smaller issues pushes
out a response to the larger issues at hand
• People are transfixed by the wrong data or indices
• More value is put on iterating narratives quickly than the
facts, their quality, and the thoughtful inferences they
imply
• Critical viewpoints are purged
• The entrepreneurial optimism that success will be just
around the next corner is linked to weaker and weaker
arguments, usually of an increasingly aspirational nature
102. THE ETERNAL LONG-TERM
CHALLENGE OF STRATEGIC
INTELLIGENCE SYSTEMS
• People come to trust those who bring forth information
that largely confirms prior views
• Those who bring forth discouraging or contradictory
information over time tend to become viewed as
misinformed or unsuited to the work, no matter how
strong the factual basis for their divergent views
103. THE ETERNAL LONG-TERM
CHALLENGE OF STRATEGIC
INTELLIGENCE SYSTEMS
• A chauvinistic intellectual and filtering bias can set in,
unless leadership signals that it actively seeks and is
willing to act upon uncomfortable truths
• Ultimately, only the CEO can protect constructive strategic
intelligence, especially in times of dissent
• Otherwise, the challenge to estimates becomes a
challenge of honesty and intelligence, and then fitness for
duty
• The need for discipline becomes greatest when
uncomfortable inferences from strategic intelligence start
impinging upon deeply held beliefs of the leaders
• Even the paranoid have to trust something , to bound
the complexity of the world in which they work
104. TAKEAWAYS
• Headcount of competitors, suppliers and distributors is the
long-term, non-financial measure of success which is most
difficult to deceive
• Staffing levels are most important to track in a landscape
composed predominantly of private companies
• Change detection is powerful
• Different information sources will be more powerful at
different phases of an industry’s growth and development
• There is a lot more information in the public domain than
most people realize, if they are willing and able to look for it,
record it, and periodically synthesize the overall picture
• Foreign language outlets, local journalism, and social media
sources provide rich sources of information, subject to care
about bias and the potential for misinformation
105. TAKEAWAYS
• Over time, an increasing volume of organized data provides a
strong ability to observe what people do, which is more
significant than what they say (except to compare with earlier
projections)
• 3rd party market research reports are often a waste of $ other
than informing the major segments and logos to track, or
entities to target as customers
• Discipline and detail in strategic intelligence can help avoid
spurious and overly localized actions, as well as
unnecessary guesswork, by having a strong grasp of all the
empirical evidence that can reasonably be obtained
• Over time, the ability to quickly add, retrieve, sort and filter
information about the strategic environment becomes more
significant than almost any one data point (no matter how
good that one point may be)
106. TAKEAWAYS
• The most valuable industry participants to track are those
that achieve and sustain the hat trick of:
1. Early (though perhaps not first) with major innovations
2. Pacesetting rate of incremental improvements
3. As zealous about reducing cost, as increasing performance
• If those three capabilities do not exist in one competitor,
ecosystem or reference class company, then
1. There is usually a significant untapped opportunity
2. Best in class performance can by modeled in hybrid from
individual players that exhibit those traits
• Benchmarking drives advancing expectations, objective
yardsticks of performance, productivity and management
performance
107. TAKEAWAYS
• Especially today with information overload and increased
risk of biased information affecting decision making,
strategic intelligence helps get people outside of any
intellectual silos they may fall into by re-grounding
discussion in evidence-based facts and likelihoods