Decision Sprint The New Way to Innovate into the Unknown and Move from Strategy to Action (for True EPUB) - Atif Rafiq

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Here is a summary of the praise and endorsements for the book “Decision Sprint”:

• Adam Grant praises the book for presenting a practical model for accelerating decisions without sacrificing quality.

• Jeffrey J. Jones II says the book puts the playbook for collective intelligence and capitalizing on ideas and opportunities into the reader’s hands.

• Kelly Campbell says they’ve seen the value of team problem solving at Google and Peacock, and this book distills best practices into an accessible and indispensable guide.

• Vishal Sikka is glad the author took the time to write down his methods so more companies can build their great futures.

• Adam Bain notes the bar for promising ideas has been raised, and every company needs a way to move faster and smarter on ideas - this book provides the guide.

• John Bryant says he has seen great ideas not get executed, and this book captures the need for both strategic and tactical thinking to move ideas to action.

In summary, the endorsements praise the book for providing a practical model and playbook to accelerate decisions through team-based problem solving, without sacrificing quality, in order to capitalize on ideas and opportunities. It is viewed as an accessible and indispensable guide for companies.

• The passage describes the need for a systematic approach to handling “upstream work”, which involves dealing with unknowns and uncertainty at the early stages of initiatives, projects, and problem-solving.

• Typically, organizations struggle with upstream work and it often feels chaotic, ad-hoc, and unstructured. This leads to difficulties making timely, high-quality decisions further downstream.

• The author proposes a system called “Decision Sprint” to systematically turn unknowns into knowns through concrete methods. This provides the clarity needed for faster, better decision-making.

• Decision Sprint can be integrated into existing workflows and project milestones. It focuses on the upstream exploration and alignment phases to connect them to the downstream execution phase.

• The book will introduce Decision Sprint and how to implement it without overhauling existing approaches. It can benefit initiatives across functions and improve organizational culture through transformed collaboration workflows.

• The book is organized into four parts: establishing the need, introducing the methodology, explaining application, and stretching future thinking on AI and management. The goal is to provide a practical yet thought-provoking solution for handling uncertainty systematically.

• The book introduces the concept of “upstream work”, which focuses on surfacing unknowns, exploring them to gain clarity, and making decisions that drive projects to successful outcomes. However, few companies have an effective method for upstream work.

• It proposes a solution called “Decision Sprint” which provides a framework and workflows for exploration, alignment, and decision-making before planning and execution. These upstream activities help simplify downstream work.

• The book details 13 workflows that teams can implement rapidly to start conducting effective upstream problem solving and decision making. This approach improves engagement, culture, and individual career growth.

• Digital tools and AI can help scale Decision Sprint across organizations. AI can analyze data from upstream workflows to provide insights and help problem solving. Use cases show how AI can help drive faster, better decisions.

• Later chapters discuss how AI may radically change the role of the CEO and strategic planning. Case studies demonstrate applying Decision Sprint to real business challenges. In summary, the book presents a practical yet theoretically grounded framework to strengthen a company’s ability to navigate unknowns and make decisions that drive growth.

• The author talks about his career journey moving from startups in Silicon Valley to C-suite roles at major companies like McDonald’s, Volvo, and MGM Resorts.

• One of his first major roles was as the first Chief Digital Officer at McDonald’s, where he helped lead a transformation to make McDonald’s a more digital business.

• He learned that transforming a large organization is as much about changing the “how we work” (culture and workflows) as it is about delivering new products and experiences.

• His approach focused on solving big problems and putting ideas into action through effective workflows. However, replicating systems from innovative companies like Amazon is difficult in more established organizations.

• Over a decade in senior leadership roles, he developed his own “system” (Decision Sprint method) for tackling unknowns, big ideas, and strategy execution through optimized workflows.

• The book aims to explain and scale this system so any team can use it to drive change from the bottom up and speed up important problem solving and decision making. The goal is to make abstract concepts immediately actionable.

• The passage describes the fragmented state of McDonald’s digital/app efforts when the author joined as Chief Digital Officer. There were over 25 separate apps across different countries and regions.

• McDonald’s was struggling with declining same-store sales and needed new growth drivers. The CEO Don Thompson hired the author to be the first CDO and lead the digital transformation.

• Internally there was skepticism that digital could be a major growth driver. Different countries/regions also had their own separate technology efforts, making collaboration difficult.

• At the author’s first major project meeting, he realized it was more of an “output meeting” where results were presented, rather than an “input meeting” to discuss assumptions and ideas. He wanted to shift to focusing more on inputs and unknowns.

• Execution culture emphasis known quantities, but innovation requires dealing with unknowns. The author wanted to “dance with the unknowns” rather than just relying on execution.

• Ultimately, the digital efforts led by the author helped drive major business turnaround and sustained sales growth through new technologies like mobile ordering, delivery, etc. on a global scale.

• The author joined McDonald’s in 2013 to help drive their digital transformation and customer experience initiatives. However, scaling new initiatives was challenging due to the culture clash between the execution-focused existing culture and the learning/innovation culture needed.

• After 3-4 years, it seemed McDonald’s appetite for change had waned. The author realized he was brought in to catalyze initial changes, but operating without fully changing the underlying culture and ways of working could only last so long.

• The author then joined Volvo as CDO/CIO. Volvo CEO Hakan Samuelsson embraced questioning and clarity of thought. He was fully engaged in meetings seeking to understand new perspectives.

• When the author suggested “clarity of thought” as Hakan’s role, he embraced it. Volvo removed titles, instead listing individuals’ main contributions.

• Hakan successfully turned Volvo around from near extinction, but then committed to bold new initiatives in electric vehicles, connectivity, autonomy. Significant culture change was needed to embrace more uncertainty and longer-term planning.

• Hakan Samuelsson transformed Volvo Cars during his tenure as CEO by focusing on direct-to-consumer sales and modernizing the company’s culture.

• He emphasized empowering teams to focus on inputs like understanding customer needs rather than outputs like sales targets. This included questioning assumptions and having exploratory discussions.

• To drive the transformation, Hakan started grassroots initiatives within existing teams rather than large-scale redesign. He worked directly with people to activate new methods through their daily interactions and experiences.

• Key tactics included introducing “input meetings” to have deeper discussions on problems and solutions, as well as printing slogans around the office promoting themes like “Bring Out the Best” to remind staff of the new focus on customers and collaboration.

• Hakan felt these hands-on efforts to change mindsets from the bottom-up were more effective than external training alone for driving real culture change at the legacy automaker. The goal was meeting Volvo where it was to modernize it for the future.

• The author had their first day as CIO of Volvo disrupted by a software glitch that halted production at the main factory producing their flagship SUV.

• They gathered the team involved in a “standup” to problem solve collaboratively, tracing issues and identifying next steps. This uncovered more clues over multiple sessions as the team grew comfortable with the process.

• The crisis offered an opportunity to bring different parts of the organization together to change culture and work through unknowns. Some leaders from this incident later became advocates for new ways of working.

• The author emphasizes the need for organizations to systematically address constant unknowns that hold strategy back from action. They propose “Decision Sprint” as a method to do this and enable innovation.

• Making decisions faster is crucial for growth, but unknowns often cause inaction, lack of commitment and frustration. Decision Sprint helps leaders and teams work through ambiguity to make better decisions.

• Teams often experience a lack of autonomy and individual accountability when dealing with complex projects involving many unknowns.

• The upstream phase of projects, before decisions are made, is important for exploring unknowns but often lacks structure and can include pitfalls like rushing to align before fully exploring issues.

• Decision Sprint provides a structured approach to the upstream phase by welcoming unknowns, conducting exploration through questioning to surface considerations, and aligning conclusions based on the exploration.

• Exploration involves sourcing diverse input through questioning to understand issues from different perspectives and fill gaps. Pitfalls can include weak exploration that misses key factors or only shallowly examines issues.

• The author advocates an approach of “thinking together” through questioning to help solve complex puzzles by placing the problem in the center and gathering contributions from all parties.

• Their “questioner personality” helps draw out different perspectives to develop a shared understanding before reaching conclusions. This approach has served them well in leadership roles involving innovations and transformations.

• The passage introduces a concept called “Decision Sprint” which is a methodology for streamlining the upstream workflow that leads to decisions within an organization.

• It outlines 13 specific workflows that comprise the Decision Sprint process, from initializing explorations to conducting decision meetings.

• Decision Sprint is presented as a way to systematically surface relevant information, drive alignment among stakeholders, and speed up decision-making.

• By following this process, teams can build a clear trail of findings to support recommendations and decisions. This transparency simplifies decision rollout and communication.

• The goal is to embrace unknowns and guide teams from strategy to execution more effectively. Decision Sprint is proposed as a way to both empower teams and shift the role of executives to higher-level calibration activities.

• Implementing Decision Sprint systematically through tools and changed norms/incentives could drive cultural transformation by changing how companies invest time and resources.

• The passage discusses the importance of “upstream work”, which refers to the early exploration and sense-making phase of projects and initiatives when there are more unknowns than answers.

• It outlines three important components of effective upstream work: exploration to surface relevant considerations, alignment to draw conclusions from what was explored, and decision-making to commit to necessary actions.

• When done well, upstream work can lead to decision points and meetings with confidence, alignment, and the right backing to then move into execution.

• However, many organizations fall short in their upstream work, treating it as an afterthought rather than a rigorous process. Common pitfalls include focusing too much on alignment without thorough exploration first, rushing to decisions without vetting options, and lacking transparency in the process.

• An effective system like Decision Sprint is needed to properly support the exploration, alignment, and decision-making components of upstream work and connect unknowns to decisions and execution in a smooth, high-quality way. This lays the foundation for successful projects, strategies and goals.

In summary, the passage emphasizes the importance of structured, rigorous upstream work to surfacing unknowns before making decisions, and introduces Decision Sprint as a solution to better support this critical phase.

• The passage discusses the concept of “alignment before exploration,” which occurs when limited understanding leads to early conclusions that are difficult to undo. This can limit big thinking and opportunities.

• It provides an example from the early days of digitizing McDonald’s, when the author pushed for exploring curbside pickup but faced resistance from executives who wanted to “align” on safer options first before exploration.

• Exploration is important to surface all possibilities and gather sufficient information to make informed decisions, rather than closing doors prematurely based on limited understanding.

• There is a tension between exploration, which allows discovery but can lack urgency, and alignment, which provides focus but risks watering down ideas without proper exploration first.

• The author advocates for “purposeful and fast” exploration to build shared understanding, rather than giving unlimited time for exploration in a lab or rushing to alignment without sufficient inputs.

• The example shows how exploration of new concepts at McDonald’s faced resistance from those wanting to limit scope, and the challenges of balancing exploration with the need to deliver tangible solutions.

The passage discusses using an upstream approach to strategic planning and project work. It advocates shifting engagement from downstream reviews of plans to more upstream involvement in idea generation and exploration.

Some benefits of upstream work mentioned include:

• Allowing leaders to better calibrate team thinking and provide guidance earlier in the process.

• Giving project teams collective intelligence from across the organization to inform their work rather than working in silos.

• Providing important stakeholders a way to meaningfully contribute inputs rather than just reviewing downstream work.

An example is given of how Jeff Jones, CEO of H&R Block, established a culture of asking questions and collaborative problem solving to bring out the best collective intelligence in the organization.

Overall, the passage promotes structuring workflows and engagement in a way that facilitates exploration, idea generation and collaborative thinking early in the strategic planning and project development process. This upstream approach is positioned as enabling higher quality outcomes.

• When Jeff Bezos became CEO of Amazon in 1997, the company was experiencing nearly a decade of flat growth.

• Bezos and his team reversed this by implementing what they called a “Connected Culture,” which prioritizes speed, trust, relationships, and teamwork. This helped drive significant growth at Amazon.

• Chapter 14 will provide more details on Amazon’s Connected Culture and how it contributed to the company’s turnaround.

• Future chapters will also discuss how AI can help CEOs by providing insights from large amounts of data. AI can track the volume of new ideas and intellectual capital being generated, evaluate project success signals, and identify areas for improvement.

• AI will give CEOs a powerful “radar” to inform decision-making by analyzing huge amounts of information in ways that would be impossible for humans alone.

The passage discusses how to approach continuous exploration within organizations as a way to stay ahead of the curve when developing new ideas or opportunities. It advocates for a three-step process:

1. Crafting a clear problem statement that captures the strategic ambiguities and doesn’t presume solutions. For Volvo’s vegan leather idea, example problem statements are given.

2. Sourcing “breadth” of input by gathering a wide range of relevant considerations or “matters” from team members to factor into decision making. For the vegan leather supply chain feasibility, example matters are listed.

3. Sourcing “depth” of input by delving deeper into each matter through research from varied sources.

The key aspects are defining the exploration goals through an open-ended problem statement, then casting a wide net to collect all relevant strategic factors through input from diverse team members before digging into each one. This process aims to thoroughly explore opportunities and keep initiatives one step ahead over months and years through continuous exploration.

• The team is given a few days to independently suggest important matters or considerations related to the problem in 1-3 word titles. This generates a list of potential matters to explore.

• Suggesting matters as questions is also acceptable, as questions can help expand the scope of what needs to be understood.

• Others cannot see each other’s suggestions until the sourcing period is complete, to avoid bias or groupthink.

• Once compiled, the list of suggested matters provides a starting point for deeper exploration and avoids blind spots.

• The list then needs to be reviewed for duplicates and clarity.

• Sharing the initial list with stakeholders builds confidence and gets their input early on.

• The next step is for each team member to generate clarifying questions for each matter, to facilitate deeper understanding and investigation of the issues.

• Questions should be neutral, open-ended, and help inform the overall problem statement. Answers should not yet be sought.

• The question list is then validated internally with the team and externally with stakeholders to ensure all important areas are covered before exploring answers.

• In 2011, the person was general manager of Kindle Direct Publishing (KDP), Amazon’s self-publishing platform. KDP was growing rapidly at 300%+ per year.

• They wanted to introduce a new program called KDP Select to solidify Amazon’s position in ebooks long-term through differentiated content only available on Amazon.

• KDP Select offered authors higher 80% royalties and other benefits in exchange for exclusivity in distributing their books through Amazon for a year.

• There were many unknowns about how to design and implement the exclusivity aspect of the program.

• The person’s team explored questions around enforcement, monitoring, and coverage of the exclusivity over many weeks to determine the smartest approach.

• Factors considered included active vs passive enforcement, book sales thresholds, monitoring costs, distribution channels covered, samples/previews, and consequences for violations.

• Through exploration of the options and issues, Amazon was able to decide on an approach that balanced incentivizing compliance while being realistic about what they could enforce at scale.

Here are the key points from the interview:

• OrangeTheory Fitness was founded by David Long and Ellen Latham with the core concept of a group fitness class led by a coach who could motivate people and help them progress at their own pace.

• Early on, David realized they needed to systematize the workout programming in a scientific way and deliver it consistently to coaches. He created a program to do this.

• They were also early adopters of monitoring heart rates during classes, which was groundbreaking at the time. Most athletes only tracked their heart rates individually.

• Having heart rate data visible to coaches and customers helped teach the importance of intensity while not overexerting. It made high-intensity interval training seem more achievable.

• These early innovations around programming workouts scientifically and integrating heart rate monitoring were critical to scaling the business and differentiating the OrangeTheory concept. It helped launch them from a startup to a $1 billion brand with over 1,500 studios globally.

So in summary, even as a very early stage startup, OrangeTheory recognized the need for systematic innovation and problem-solving through things like structured workout programming and leveraging emerging tech like heart rate monitors. This helped them grow tremendously.

Here are the key steps to running an effective alignment process:

1. Collect conclusions independently from the core team. Have each member reflect on an exploration (e.g. FAQs) and submit their conclusions individually. Encourage multiple conclusions as strategic direction often has layers.

2. Scrub and merge conclusions. The team leader reviews all submissions and combines similar conclusions, removing duplicates.

3. Share conclusions with team. Distribute the compiled list of conclusions for all to review before discussing. This establishes a common understanding.

4. Facilitate discussion. The team leader leads an open discussion allowing members to discuss, debate and refine the conclusions. Seek agreement where possible.

5. Capture alignment and gaps. Note conclusions the team clearly aligns on as well as any areas of disagreement or lack of clarity. Having this visibility helps focus resolution.

6. Resolve gaps as needed. For notable gaps, dive deeper into objections, test assumptions, bring in others as needed to reach resolution and agreement.

7. Involve broader stakeholders. After establishing agreement within the core team, socialize the conclusions with relevant stakeholders and adjust as needed based on feedback before finalizing.

The key is establishing a structured yet collaborative process to systematically gather inputs, surface both alignment and gaps, then work to resolve disagreement to get to clear agreement across the initiative team and key stakeholders.

The key points are that alignment work should be done asynchronously where possible to save time. This includes collecting conclusions from the team remotely and having them vote on the conclusions to generate a “heatmap” of alignment. This heatmap shows where consensus exists and where further discussion is needed. It removes personal biases and provides objective data.

Once the asynchronous work is complete, the team can meet to review the voting results. They can quickly validate areas of agreement and focus discussions on areas of divergence. Testing assumptions with data can help build alignment by addressing any gaps.

Preparing content for socializing the conclusions is important. Written questions and answers or FAQs are recommended over PowerPoint to encourage clear thinking. The content should describe the topic, include the FAQs and conclusions categorized by agreement level.

Finally, socializing the conclusions involves sharing the content and getting sponsorship from key leaders. This expands the level of alignment in the organization and prepares to move the work forward to action. Buy-in from above is important even if day-to-day work was aligned internally.

The passage discusses socializing knowledge and seeking alignment after an exploration or initiative is completed. It recommends that project teams go on a “roadshow” to meet with executives and share what was learned from the exploration.

The approach is to focus on knowledge sharing by explaining “what was learned,” “what was reasoned through based on the learning,” and “what conclusions were produced.” The goal is to get input from leaders like “what did we miss?” or “would you modify anything?” rather than just presenting a fully packaged plan.

This approach tends to make alignment “ridiculously easy” as leaders see the difference compared to initiatives where exploratory methods were not used. Teams are coming with understanding rather than just looking for approval.

When conducting these meetings, the passage advises tailoring the approach based on company size. In larger companies it may involve a formal steering committee with preliminary individual meetings with committee members. This allows leaders to better understand the work in private before group discussions.

The key benefits of socializing knowledge this way are shared understanding, support, commitment and advocacy for the initiative. It spreads understanding when done well and gets people working from the same information base before decision making. While not always guaranteed, it is generally very effective.

The passage then provides four sample FAQs that could be part of an exploration on launching an exclusivity program for authors on Amazon. It discusses how conclusions could be drawn from the exploration and reasons provided to back each conclusion.

• The company explored launching an exclusive program for authors on Kindle that would give authors higher royalties if they agreed not to publish their books elsewhere.

• Through the exploration, they identified several issues like needing to scale up monitoring/enforcement of exclusivity agreements and foreseeing much higher volumes of titles that would need reviewing.

• The key conclusions were that tools would need to be developed to automate content review at scale, and they would need to estimate future volumes to plan contractor hiring during tool development.

• The proposed actions included brainstorming an MVP scope for automation tools, reallocating engineering resources to build the tools, and forecasting review volumes to plan contractor hiring.

• These actions were proposed to the decision-makers for input and approval to move the initiative forward into the execution phase. Ongoing exploration would then focus on defining the offering and subscription details to continuously progress the initiative.

• Volvo offers a wide range of car models and configurations, from SUVs to sedans to wagons, but having too many configuration options makes it difficult to efficiently produce and deliver vehicles to customers.

• For a car subscription service, it makes more sense to limit options to a smaller number of packages similar to how iPhone options are structured (e.g. storage size options rather than endless customizations).

• Packages would need to consider features like leather, sound system, sensors to make cars desirable, as well as a limited number of colors and trims.

• Newer models like the XC40 which appeal to millennials could be prioritized since they have the latest tech and design.

• Pairing a subscription with a “cool” car model may appeal to the target customer demographic.

• Once decisions are made, new unknowns will surface, so companies need to continuously explore the next set of relevant issues to better understand opportunities and risks.

• Bringing focus to the next explorations after making decisions helps establish continuous exploration as a “deep ritual” and core capability.

• Reviewing past explorations and previewing upcoming areas of exploration builds the habit of ongoing discovery and preparation that readies an organization for what’s ahead.

• Providing space for teams to explore opportunities and propose solutions is important for innovation. This allows them to deeply research problems, benchmark solutions, and test ideas through rapid prototyping and validation with customers.

• When testing ideas, focusing on short-term milestones and routines to track progress helps determine if an idea is on the right track or needs adjusting. Tim Hortons tested a conveyor belt drive-through solution in this way.

• Gaining confidence in proposed solutions comes from spending hands-on time understanding operational details and getting customer and franchisee feedback through research, concept testing, and focus groups.

• Passing on opportunities after exploration is normal and should be transparent. Decision Sprint provides a framework for adequately canvassing an opportunity and killing weak ideas without overburdening senior management. Both passes and approvals serve the purpose of exploration.

• A data-driven and experimental approach to digital transformation allows for quick, objective testing of hypotheses without theoretical debate. Leaders who advocate this approach can bring organizations to the next level.

Here is a summary of the key points from the interview:

• Julia Vander Ploeg emphasizes the importance of giving teams the space to experiment and test hypotheses rather than pushing for immediate certainty and delivery. She argues this allows teams to be smarter and learn more quickly.

• It can be challenging for leadership to embrace uncertainty and provide time for learning rather than demanding set roadmaps and timelines. But it enables teams to crack new ground and push boundaries.

• Leaders need to shift from solely leading through authority to more coaching-focused leadership that empowers teams to experiment and make discoveries.

• She discusses an example of McDonald’s rapidly deciding to partner with Apple to support Apple Pay on launch. They only had a few months to upgrade all US restaurants, so couldn’t follow a formal Decision Sprint process.

• Zaki Fasihuddin discreetly explored the operational feasibility and partnership terms without a full team. They tested hypotheses rapidly to determine what was possible in the short timeline.

• It highlights the challenges but also opportunities of moving quickly when circumstances demand rapid decisions without the ideal decision-making process.

Here is a summary of the key points from the information provided:

• McDonald’s was well-positioned to be a launch partner for Apple Pay since most of its payment terminals were already NFC-enabled from prior investments in contactless payment technology. However, some upgrades were still needed.

• A major challenge was enabling contactless payments in the drive-thru without significantly increasing transaction times, as speed of service is crucial. McDonald’s tested extending payment terminals on articulating arms through the drive-thru window.

• Extensive testing and modifications were made to payment software and hardware to ensure functionality and performance at scale across 14,000 US restaurants on launch day. A dedicated “tiger team” coordinated the effort.

• While some concerns existed about operational impacts, leadership emphasized this was part of McDonald’s digital transformation and optimized solutions would be found. Hands-on training also helped prepare employees.

• Being an Apple Pay launch partner provided branding and partnership opportunities for McDonald’s and helped establish it as an innovator in digital payments experiences. Overall, the effort strengthened McDonald’s technology capabilities and customer offerings.

So in summary, McDonald’s successfully enabled contactless mobile payments across its large footprint through coordinated technology and process changes, while addressing challenges like maintaining drive-thru efficiency. This positioned it as a leader in digital payment acceptance.

Here is a summary of the key points about Workflow #1 - Initiating an Exploration:

• The purpose is to craft a clear problem statement that defines the major decision or fork in the road facing the project/initiative.

• Inputs are identifying the relevant competencies (knowledge, perspectives, roles) needed to explore the problem.

• The output is finalizing the problem statement and identifying the initial working team based on competencies.

• Core participants are a problem statement author/champion, key stakeholders, and potential working team members.

• The champion helps recruit the right initial working team by socializing the problem statement and compelling potential members of the relevance of their perspectives.

• Getting early buy-in and sponsorship from a champion is important to get the exploration launched effectively. Their energy can help get others invested and make it feel like something worth contributing to.

So in summary, this workflow is about setting the stage for the exploration by defining the problem clearly and constituting an initial working team with the right mix of competencies to dive into exploring possible solutions.

Here is a summarized version with more details:

Building an Effective Exploration Through Champions

Effective exploration of new ideas and opportunities requires a champion to lead the process. The champion’s key roles include establishing a starting point, defining next steps, and bringing together the right people. It is critical for the champion to quickly operationalize the exploration to build momentum.

Exploration works best when the champion brings together diverse perspectives to collectively develop the initial idea. This is like building a snowman - you start with a small base and keep adding more snow and materials to make it bigger and stronger. In the same way, an idea is strengthened by input from different functions and viewpoints.

For example, if a business is considering entering a new market, the exploration must look beyond any one function to consider the broader market landscape, consumer behavior, partnerships, marketing strategies, technology needs, product experience, and more. The champion ensures all relevant aspects are incorporated to create a cohesive exploration and business plan.

At the initiation stage, the champion can share the exploration process with sponsors to build transparency and trust. Key steps involve validating the problem statement through discussion, identifying core competencies needed to address the problem, and setting expectations for progress.

The exploration then builds out by sourcing relevant matters or topics to ensure all important considerations are covered. Sourcing also involves collecting clarifying questions to delve deeper into each matter. Separating the sourcing of matters and questions allows the team to focus independently on breadth versus depth.

The champion then facilitates a working session where the team evaluates the proposed matters and questions, identifies any expertise gaps, and decides how to fill those gaps. The overall goal is to continuously strengthen and expand the exploration through inclusive collaboration led by the champion. This helps maximize the chances of success in addressing the problem at hand.

The passage discusses the importance of a second iteration of question sourcing as part of the decision exploration process. Doing a second round of sourcing allows the team to focus on adding more questions in areas that lacked depth originally, based on insights gained from previous workflows. Bringing in additional experts during this second round can help address any blindspots.

It then talks about assigning specific point people to answer each question, as well as having reviewers for each answer to provide additional perspective and catch any blindspots. Having a point person and reviewers acts as a check and balance.

The goal of calibrating the exploration in this way is to end up with a strong, comprehensive canvas of matters and questions to explore. This positioned the team well to share the exploration framework with senior executives beforehand to gain trust and buy-in before answering any questions.

In summary, it advocates for repeating the question sourcing activity with the benefit of hindsight and insights from previous workflows, in order to strengthen the exploration framework in a targeted way before proceeding to answer questions.

• The passage discusses different workflows involved in the Decision Sprint process, which helps teams solve problems collaboratively through exploration and consensus-building.

• Workflow #9 involves socializing the team’s work and conclusions with key stakeholders to get them aligned and supportive of the proposed direction. This involves presenting a “CliffsNotes” version of their exploration and recommendations.

• Workflow #10 aims to solidify alignment by getting stakeholders to nod their heads in approval of the recommendations and transition to action mode.

• Workflow #11 involves identifying concrete decisions by canvassing people involved in execution and gathering specifics on timing, costs, roadmaps etc. for each recommendation.

• Workflow #12 is about preparing compelling content like FAQs, narratives or demos from the exploration phase to prepare for decision meetings.

• Decision meetings get to the “yes” or “no” on specific decisions, committing resources and marking the start of execution based on approved decisions. Content helps decision-makers understand how the team arrived at their recommendations.

So in summary, it discusses different workflows in Decision Sprint aimed at building consensus, identifying decisions and preparing for formal decision meetings to commit to action.

• Decision meetings follow an efficient format as senior executives have a busy schedule. Teams typically only have 15-30 minutes to present recommendations.

• The focus is on the specific decisions rather than high-level recommendations. With proper alignment, the recommendations are more likely to be on target.

• Executives will want to vet details like budgets and scope further. They may propose alternatives or trade-offs that consider higher-level company factors beyond the project.

• The best outcome is when executives link the decisions to their own higher-level decisions needed to support the project. They take ownership of follow-through on dependencies.

• After decisions are sorted, previewing the next exploration topic establishes continuous exploration as the norm. This roots the behavior of continuous exploration and decision-making in the organization.

• Taglines or shorthand phrases can effectively represent and communicate the value of workflows to shape organizational culture. Pairing workflows with taglines accelerates cultural shifts.

• Examples of taglines introduced include “Frame the Problem”, “Exploration Before Alignment”, “Group People Around Challenges”, “Input Obsession”, “Embrace Unknowns”, “Preview the Work”, “Calibration over Control”, “Dive Deep”, and “Seek to Understand”.

So in summary, the key aspects covered are how decision meetings should be run efficiently, the focus on decisions versus recommendations, and how taglines can reinforce the cultural impact of workflows when properly paired and communicated.

• The passage discusses how to apply the Decision Sprint methodology to improve common meeting types like kickoffs, brainstorms, planning meetings, deep dives, project reviews, strategy sessions, and executive reviews.

• It introduces the concept of a “flow state” for projects, where the rate of moving from unknowns to knowns keeps up with expectations at each milestone. Decision Sprint is designed to create this flow state.

• For kickoffs, it suggests focusing the meeting on agreeing to a concise problem statement, as outlined in Workflow #1. This differs from typical kickoffs which may not clearly define the problem.

• It will provide suggestions for how to apply the various Decision Sprint workflows to improve each of the common meeting types and help teams achieve a flow state with fewer, more effective meetings.

• The overall goal is to help teams make more progress in less time by streamlining meetings and orchestrating milestones more calmly through the use of Decision Sprint processes.

So in summary, it introduces how Decision Sprint can be applied to existing meeting types to better define problems, make more effective progress, and achieve a desirable flow state for projects and problem-solving efforts.

The passage discusses planning meetings after conducting a brainstorm to source input for building an exploration. It emphasizes the importance of having clear and complete input to guide follow-up actions and the exploration process. If the brainstorm was chaotic and did not properly canvass the breadth and depth of matters and questions, then the subsequent planning will be inadequate.

Good planners should reflect if the brainstorm outputs are sufficient. If not, they should rerun the brainstorm workflows in a more structured way to fill gaps. This involves clarifying what key matters need to be explored, possible risks or failures, and questions to investigate each matter deeper. Planners also scrub the input to refine wording, identify duplicates, and assign questions to collaborators, including seeking relevant perspectives from across the organization. The goal is to have well-defined exploration inputs to guide effective planning and execution of follow-up actions.

The passage discusses best practices for ongoing project reviews and interactions between project teams and senior stakeholders/executives. It emphasizes the importance of transparency into the exploration process from the beginning.

Rather than just providing status updates, teams should share the concrete knowledge and insights gained from exploration activities like deep dives and question answering. This helps socialize the team’s working knowledge and ensures everyone is on the same page.

Strategy sessions with the working team should involve actively discussing and deriving recommendations together, rather than one or two people packaging them first. This allows for better alignment within the team.

Executive reviews then focus more on strategic dialogue and fine-tuning recommendations, rather than re-explaining the work. If timing requires covering alignment and decisions together, spacing these interactions out ideally is preferred.

The overarching message is that transparency into the exploration process from early on helps smoothen interactions down the road between teams and leadership. Sharing insights continuously keeps everyone working from a shared base of knowledge.

The key roles involved in initiatives using Decision Sprintworkflows include the C-level executives, sponsors, and working team.

The working team is responsible for sourcing input, building explorations, running explorations to feed recommendations, conducting alignment sessions, and preparing for decision-making meetings. They manage the day-to-day processes.

The project leader ensures the exploration meets standards, validates timelines, drives recommendations from the exploration, leads alignment sessions, and sets a high bar for decisions.

The project admin plans workflows, initiates input sourcing periods, and curates input to be actionable for the exploration.

All working team members should transcend their functional silos and represent the company’s overall interests. They solve problems collectively rather than as representatives of individual roles. Decision Sprint simplifies processes for project leads and helps all roles work toward common goals and milestones.

• Assign tasks to team members for exploring different aspects of the proposed project.

• Provide regular project status updates and timeline updates in reviews. Report on the progress of various workflows.

• Work with the project lead to resolve any issues or bottlenecks that arise in the timeline.

• Develop informative content from the exploration work to facilitate alignment between stakeholders and inform decision making.

Here is a summary of key points about problem-solving from the passage:

• As an intrapreneur or change agent within a large organization, you need to be able to solve problems creatively with limited resources. This may involve convincing others to help and finding ways to cobble together support.

• It’s important to be able to articulate a clear vision and story for new initiatives to gain support. You need to address potential objections andunknowns upfront through analytical problem-solving.

• Methods like the Decision Sprint can help intrapreneurs and skeptics address unknowns constructively. It provides a process for surfacing issues, exploring alternatives, and building clarity and commitment to action.

• Pragmatists play an important role by surfacing practical obstacles, but they need to do so in a solution-oriented way rather than just raising objections. Their insights are valuable if they remain neutral at first.

• Change agents can be effective partners for intrapreneurs if they understand the company culture and can open doors. Speaking the “language” of existing operations helps drive novel ideas forward.

• Effective problem-solvers roll up their sleeves, engineer solutions around blockers, and tell a clear story to motivate others. They address doubts proactively through reasoning and data.

Here are the key takeaways:

• The companies used their owned restaurants as testing grounds for new concepts, both to generate revenue and to test ideas before sharing them with franchise operators. This helped validate concepts and avoid pushing ideas that didn’t work.

• When a new executive (Atif) was brought in with a different perspective, his role was to stretch the company’s thinking beyond just making hamburgers. The CEO recognized the business needed to extend itself to maintain the #1 position.

• James, one of the executives, played an important role in building support for new ideas by aligning management, franchisees, and leveraging momentum for changes.

• In summary, the company used owned restaurants to test new ideas, recognized the need for new perspectives to drive innovation, and focused on building alignment across stakeholders to successfully implement changes.

• Decisions Sprints is a methodology that teams can use early in a project to explore problems, build alignment, and make decisions. It involves structured workflows to source input, define the problem space, and develop recommendations.

• Decision Sprints should be applied when there is a meaningful but still emerging problem statement. It provides a way to get ahead of issues before they stall progress.

• A Decision Sprint can be initiated by the project sponsor, a team leader, or even a pre-project team without formal sponsorship yet.

• For initial adoption, teams need to commit to running through at least one full life cycle (exploration to outputs) of 90 days, appoint a strong program leader, and get participation from the core working team.

• Organic adoption happens as teams experience benefits like more streamlined work, smarter recommendations, and less effort required. Word then spreads naturally.

• Senior leaders can further promote adoption by establishing the right language, linking Decision Sprints to project milestones, and connecting it to cultural transformation efforts already underway. The goal is for it to become a standardised practice.

• Digital tools can make the Decision Sprint process more convenient for everyone involved by managing tasks, timelines, notifications, and input collection in a centralized digital interface. This reduces the administrative burden.

• They allow teams to do more work asynchronously by shifting activities like input collection, commenting, and question answering online. This reduces meeting loads.

• Digital tools help remote teams remain highly collaborative by facilitating asynchronous participation and visibility into the exploration process.

• The data generated from activities in digital tools, like who contributed what inputs and answers, can enable analytics and eventually AI insights to improve the process over time.

• Implementing digital tools likely involves setting up templates and interfaces for key activities like matter and question input, exploration overviews, question answering, and output content generation in standard formats. This automates documentation and improves transparency.

• Security, accessibility, and ability to comment/review are also improved with digital implementations compared to disjointed offline documents and meetings.

So in summary, digital tools bring major convenience and collaboration benefits to Decision Sprint while also creating new data sources to optimize the process through analytics and AI in the future.

• Decision Sprint workflows can be enhanced through integration with common collaboration software like project management (Trello, Asana, Jira), brainstorming (Miro, Figma, Overflow), and messaging (Slack, Teams) tools. This allows information to flow between different stages of work and from unstructured to structured activities.

• Decision Sprint lends itself well to asynchronous work models where team members can contribute independently according to their own schedules. Digital tools enable asynchronous input, review, and coordination without needing meetings.

• Tools that digitize Decision Sprint processes provide a sense of belonging for remote/hybrid teams by making all contributions visible in one place. This reduces bias and better recognizes contributions.

• Digitizing work reveals previously hidden data that can be analyzed to gain insights. Things like voting patterns and recommendations can be studied quantitatively rather than just perceiving the “room.”

• The author advocates using purpose-built software with Decision Sprint baked into the workflows, rather than generic tools or custom in-house solutions. Ritual is mentioned as one example built specifically for this approach.

• AI and algorithms could help manage strategy and innovation like an advanced “mission control,” learning from data generated through digitized processes to help companies move faster and smarter.

Here are the key points from the summary:

• Amazon has established an innovative management culture through how it defines leadership roles and allows learning through observation, rather than formalizing workflows.

• The chapter explores what could come after Amazon in terms of management approaches, focusing on more AI-driven approaches that leverage analytics and AI to help managers determine project status and progress.

• It introduces the concept of “mission control”, which uses higher-level understanding enabled by metacognition/analytics to assess how well teams are progressing initiatives.

• AI can team up with humans to perform activities like management more effectively and efficiently, for example by suggesting next steps.

• Analytics involve creating meaningful data constructs for humans to assess progress, while AI finds its own patterns and makes suggestions.

• When initiatives are digitally tracked, a wealth of useful data is generated that can be leveraged for analytics and signals on initiatives.

• Mission control focuses on developing signals by comparing specific initiatives to samples/benchmarks, to catch problems early before they grow.

• Some simple example analytics are discussed, like measuring team exploration confidence against benchmarks to identify need for more iteration.

• The authors want to use data and AI-powered analytics to gain insights into how successful exploration, stakeholder alignment, and decision-making processes are for projects. This would help spot and correct issues early.

• Data would come from running initiatives through a process like Decision Sprint that collects feedback and metrics at various stages. With a large dataset over time, AI could find patterns.

• For exploration, AI could analyze similarities between initiatives, outcomes of past projects, and current feedback to assess if exploration is on track for success. It may provide clues on weak areas to strengthen.

• For alignment, AI could compare levels of agreement on conclusions to benchmarks from similar past initiatives. It could determine if the current level of alignment is high enough or risks issues down the road.

• These AI-driven predictive analytics aim to alert managers to potential problems before they become serious, helping them focus efforts where most needed. The goal is using data and AI for more objective, error-correcting management versus relying on opinions.

In summary, the authors see great potential for leveraging big datasets, AI, and predictive analytics over time to gain insights that can proactively spot issues and guide management decisions. This aims to make management more fact- and error-correction driven.

Here are my key takeaways from the provided summary:

• AI can help assess project alignment and success by analyzing hidden patterns in data like support levels for recommendations, correlation with outcomes, etc. This can give more confidence than individual voices and provide a more objective view.

• AI can also help determine when decisions are ready to be made by analyzing patterns in past initiatives - looking at things like quality of exploration, level of alignment achieved, and timing of decision points and their outcomes. If current work meets thresholds seen in successful past cases, it suggests readiness.

• For specific decisions, AI can learn from retrospective analyses to refine how different factors/stakeholders should be weighted. Over time it can score individuals’ judgments based on track record to inform future influence.

• In general, AI enables more explainable, data-driven management by providing insights across initiatives, signaling what needs attention, and refining key workflows like determining alignment, readiness and optimal decisions. It forms a partnership with humans rather than replacing judgment.

The key benefits are presented as more objective, evidence-based management through AI’s ability to uncover hidden patterns across data, learn from past cases, and surface insights to inform key workflows and oversight. There is an emphasis on AI enhancing rather than replacing human decision-making.

Here is a summary of the key points from Chapter 14, “The Upstream CEO”:

• The chapter discusses how management can use dashboards to gain more objective insights into where project teams and initiatives may be stuck or facing challenges, rather than relying on guesswork and hearsay.

• Dashboards would provide data on factors like confidence levels, alignment, and pace/velocity of initiatives to help identify where management attention and support is most needed.

• Management can use these insights not just to address problems but also to accelerate successful initiatives and continuously improve workflows and decision-making processes over time.

• Data science plays a role in generating the dashboards by analyzing data from digital tools and processes used in upstream work. This provides visibility into how upstream work is unfolding.

• The production of new “intellectual capital” in the form of frequently asked questions (FAQs) and answers is discussed as a potential indicator of future success that data science models could analyze.

• The chapter explores how blockchain and AI could help ascribe quantifiable values to this intellectual capital, potentially changing how companies are valued based on their upstream initiatives and innovation pipelines.

• The expected value calculations for initiatives coming from upstream work need to incorporate factors that could discount or increase the expected value. External events or changing conditions could impact the potential value.

• Assigning quality scores and importance to initiatives is subjective. Companies need objective approaches and independent reviews to help evaluate initiatives.

• Historical data on similar past initiatives is needed to feed AI models and improve forecasting. More data is required over time to develop accurate models.

• Blockchain can help provide transparency and assurance around the data used to evaluate initiatives. It prevents manipulation and forces management to acknowledge reality.

• In the future, intellectual capital from initiatives could potentially be traded on blockchain-based marketplaces, allowing companies to monetize ideas even before full implementation.

• AI could help quantify individual contributions to initiatives more precisely for performance reviews and talent planning purposes. This would provide a more objective evaluation of skills and strengths.

• With more data, AI can help match company needs to employee capabilities and identify gaps to address in hiring and recruiting. This helps optimize the mix of skills and judgments within organizations.

So in summary, the key enabler for AI-powered valuation and management is obtaining more objective and historical data on initiatives, contributions and outcomes through approaches like Decision Sprint and blockchain-recorded data. This data can then be leveraged by AI models to improve forecasting, evaluations and planning.

Here are some key points from Jeff Jones’ discussion of communication and management style during transformations:

• When he became CEO of H&R Block in 2017, the company was going through a transformation to modernize its business model and technology.

• Early on, they identified four big strategic initiatives and made sure everyone in the organization understood them clearly. Regularly communicating progress and wins helped build momentum.

• He focused on listening to employees at all levels. This helped surface challenges and ideas to overcome obstacles to the transformation.

• Storytelling was important to painting a picture of where the company was going and why. This helped employees understand their role and buy into the vision.

• Regular “All Hands” calls and meetings, as well as one-on-ones, ensured everyone stayed connected to the strategic priorities and overall direction.

• Celebrating milestones and recognizing individuals who contributed helped sustain energy and motivation over the multi-year transformation effort.

The key takeaway is that clear, consistent and two-way communication was crucial for Jeff to lead H&R Block’s cultural and business model transformation by engaging employees at every level.

Here are the key points about how an ambitious CEO might use their time when organizations embrace upstream work and AI enables new capabilities:

• Driving valuation by using AI to better understand how upstream initiatives will create value over time, beyond just operational forecasts. This provides a holistic view to assess valuation.

• Strategic planning becomes more data-driven and connected to day-to-day work with AI. AI can help align growth ambitions, strategic pillars, and talent/workforce planning by quantifying needed talent pools and profiles.

• Calibrating upstream initiatives through an AI-based “radar” that continually evaluates how initiatives are unfolding and translating into plans, recommendations, and value. This provides better guidance on initiatives.

The flywheel effect is that driving valuation informs strategic planning, which then guides calibrating initiatives, with each area informed by and informing the others via AI capabilities. This allows the CEO to focus on high-level moves like ensuring proper talent and resources are in place to execute ambitious strategic plans.

creation of, 185–187

digital, 185

AI as, 185–188

vs. human, 187f

Assumptions:

challenging, 42, 49

uncovering and testing, 7

Attention economy, 81–84

Audacity and authority personas, 211–212

AWS, Amazon Web Services, 23

Baby boomers, 87

Bandwidth management, 234–235

Bargain of inclusion, 184

Behavioral science, 2, 38–44, 198

Beginner’s mindset, 35

Bennis, Warren, 203

Bias avoidance, 39–42, 49, 139

Big Data, 176

Bio:

elements of, 188–189

written, 187–188

Blind spots, confronting, 42

Brainstorming, 133–135

Breakthrough performance, 3

Business development, 164

Calendar:

blocked time on, 79

setting meetings on, 25–26

Carbon five, 21

Career transitions, 200–201

CenturyLink, 18

CEO, 14–15, 298–301

responsibilities of, 25

role of, 293–299

Change:

exploring, 131

managing, 199–208

radical, 200–201

resistance to, 202

Chaos Monkey, 22

Check-in questions, 25–26, 92, 235

Checkouts and check-ins, 185

Citrix GoToMeeting, 23

Closed-loop learning, 113, 253

Coaching, 96, 123, 179, 200

Collaboration:

defining, 16

digital, 21–22

enhancing, 33

with goals, 95, 165

intensive, 82

keys to, 22–25, 127

levels of, 16f

-by-objective model of, 21f

-oriented culture, 127

Communication:

building, 200

effective, 25

in feedback loops, 113–115

importance of, 23

modes of, 23f, 29f

Community, 16, 82, 237

Companies, types of, 15–18

Compensation, 104–105

Complacency avoidance, 36

Conclusions, collecting, 102

Conflicts of interest, 38–39

Connecting the dots, 164

Constraints, 128, 131, 158–159

Constructive criticism, 117–118

Consumerization of IT, 23

Contribution metrics, 104–105

Controls, 58, 128

Core qualities, developing, 206

Corporate culture, 199–202

Costs of fear, 204–205

Courage, 202–206

Creating pull, 64–69

Creative destruction, 200–201

Creativity:

blocking time for, 79–84

harnessing collective, 131–136

leveraging diverse, 130–131

sparking, 129–130

teams and, 33–34

tribes and, 127

Crosby, David, 203

Curiosity:

importance of, 5, 33, 188

institutionalizing, 66–67

sparking, 35

CVS MinuteClinic, 17

Cycles:

short, 68–69, 254

of thought, 58

Decentralization, 18

Decision-making:

improving, 123

individual vs. group, 56

radical, 65

shared vs. top-down, 20

simplifying, 24

Decision Sprint:

benefits of, xiii-xiv

core practices, 6-9

integrating with AI, 275-279

origins of, xii

as a system, xiii, 275-279

Decision sprints, running, 119–124

Decompression time, 79

DellEMC, 18

Deming, William Edwards, 112

Dendrite, 131

Demographics, global shifts in, 87–88

Design thinking, 133

DevOps movement, 13, 20

Digital assistant creation, 185–187

Digital tribalism, 82, 129

Disagreement cultures, 201–202

Discovery process, 6–7, 48–50, 58–62

Disney, Walt, 101, 129

Distractions, managing, 26, 78–84

Divergent thinking, 132

DNA sequencing, 175–176

Dougherty, Dale, 20

Dropbox, 21

Dweck, Carol, 204

Early adopters, 213

Earlyvangelists, 213

eBay, 21

Ebola outbreak (2014–16), 179–180

80/20 rule, 108

Einstein, Albert, 132, 136

Emotional intelligence, 204–205

Employee engagement, 104–105, 199–200, 214–217

Employee experience movement, 215–217

Employee incentives, 215–216

Engagement levers, 215

Entrepreneurial spirit, 21

Error seeking, 58

Ethics in AI, 279

Evaluation framework, 51–57, 159

methodologies for, 51f

types of decision methods, 51

Eventbrite, 21

Evidence-based management, 111–113

Excitement building, 69

Execution:

focusing on, 14

importance of, 113, 298

levers of, 209

planning vs., 5

Exploration:

alignment’s relationship to, 44, 47

assessing, 47–51

conducting, 133–136

definition of, 7, 44

initial phase of, 48

managing, 106–108

shifting to wider, 44

vs. exploitation, 47

Explorer personas, 209–210

External motivation sources, 104

Failure:

learning from, 113, 202

tolerating, 203

Feedback loops, 111–115

closed-loop, 113, 253

continuous, 112

creating intentional, 114

importance of, 112–113

integrating decision sprints into, 253

leveraging micro-, 113-114

open-loop, 113

Fear cultures, 204–206

Feedback:

constructive, 117–118

giving clear, 25

seeking, 42

sharing negative, 117

Filtering information, 109–110

Ford Motor Company, 101–102

40 Steps methodology, 52–53

Franchise structures, 20

Functionality matrix, 144–145

Future, exploring the, 131–136

Future of Work, The (Greene), 88

Gathering Ideas phase, 109–110, 115

General Electric, 101

Generation X, 87-88

Generations, evolving expectations of, 87–88

Generation Z, 88

GFPQ technique, 157–158

Global shifts, coping with, 86–89

Goals:

defining/setting clear, 21, 58, 69, 120–121, 165

revisiting, 25, 94

Goh, Khim Yong, 179–181

Google, 21, 23, 28, 207

Gratitude practice, 204

Greene, Harry J., 88

Group decision-making, 56

Groupthink avoidance, 201

Growth and innovation, balancing, 20

Habits:

building new, 28, 207–208

unlearning, 28

Hammer, Michael, 11

Harmonization, 164–166

Hassan, Amir, 179–181

HBR Ascend, 183

Health care system model, 16–18

Hi-po pursuits, 101, 165

Hmong refugees, 180–181

Home depot, The, 21

HP, 13, 20

Hulbert, Mark, 68

Human-AI partnership, 275-276, 278-279

Human-centric design, 186

Humility, 35, 202

Hyper-convergence vendors, 18

Ideas generation, 129–136

Ideation methodology, 133

Ideation phase, timing of, 109

IDEO, 133

Imageboard websites, 82

Implementation:

executing, 143–145

key to, 122

monitoring and improving, 122–123

of proposals, 122–123

Importance vs. urgency matrix, 158–159

Inclusion, 184

Incubation time, 79, 134

India’s digital revolution, 88

Individual change and organizational change, 199–208

Individual vs. group decision-making, 56

Industry shifts, 86

Information:

filtering, 109–110

overload of, 81, 109

sharing key, 24–25

Sources of, 26, 38

Innovation:

and creativity, 127–136

focusing on purposeful, 20-21

importance of, 20

network effects of, 21

strategic enablers, 21f

Insight cycles, 68–69

Instagram, 21, 23, 82

Institutionalizing practices, 66–67, 82, 214–217

Insurance company model, 16–18

Integration management, 164–165

Intel, 207

Interaction modes, 29f

Interests, aligning, 39

Internet access, global, 87

Intuition, harnessing collective, 134

Investment banking model, 16

iPhone, launch of, 68

Issue discovery, 60–61

Job design:

and the future of work, 88–89

trends in, 16

Jobs, Steve, 68, 101, 207

Johnson & Johnson, 203

Kaminski, Michael, 179–181

Kanban methodology, 124

Key result areas (KRAs), 104

Keywords, finding right, 24, 108

Knowledge and wisdom, 5

Kodak, 15, 201

Landry, Ryan, 179–181

Leadership:

distributed, 20

emergent, 20

evolutionary nature of, 207–208

qualities of great, 202–206

responsibilities of, 3, 25, 299

spectrum of styles, 18–20

Learning:

accelerating collective, 66–67, 215

closed-loop, 113, 253

continuous, 111–115

organizational, 113

Learnings phase, 119–120

Leef, Eric, 179–181

Life stages model, 89–90

Liker, Jeffrey, 203

Listening deeply, 25, 34–35

Looking for meaning phase, 119

Luenendonk, Ralf, 21

Lyft, 21

Maersk, 18

Management by objectives (MBOs), 120–121

Management levers, 209–210

Management practices for accelerating growth, xii-xiii

Management system requirements, xiii-xiv

Manager personas, 210–211

Mankins, Michael C., 164

Market insights, gathering, 37–38

Marketing execution, 143, 167

Maslow’s hammer, 11-12

Matrix view, 145-146

McDonald’s, 101

Meditation, 79

Meetings:

blocking time for, 79

practicing purposeful, 25–26, 156

Mentors, recognizing, 123

Mercedes-Benz, 101–102

Merton, Robert C., 21

Metrics that matter, 223

Micro-feedback loops, 113–115

Microlearning, 217

Microsoft, 18, 21, 23, 26

Military principles:

for management systems, xiii

at SAS, 18

Millennials, 87–88

Mindset for innovation, 35–36

Mindsets, fixed vs. growth, 204

Mission statements, 121–122, 159–160

Mission control, 258–261

Mistakes:

learning from, 114, 203

tolerance of, 203

Mobile technology and digital tribes, 82

Modern family life stages, 89–90

Momentum, building, 69

Morale improvement, 198–199

Morris, Errol, 132

Motivation, internal vs. external, 104

Movement builders, 164

Myers-Briggs personality inventory, 126

Netflix culture, 127–128, 202–203

Neuroplasticity, 204

News Corp, 20

New York Times, The, 21

Nike, 17, 101

No fear culture, 203–206

Norming stage of teams, 125–126

Northrop Grumman, 18

Objectives:

agreeing on, 120–121

developing, 120

sharing weekly reviews of, 25

Obstacles:

facing, 204–205

identifying and overcoming, 131

Open-loop learning, 113

Opinions vs. data, 39

Opportunity analysis, 37

Organizational change, 198–208

Organizational design:

dynamic, 17–20

future of, 16–21

models, 16–18

Outcomes and outputs, 104–105

Overcommitment avoidance, 69

Ownership, spreading, 20

Pace layers, 76, 93

Pareto principle, 108

Partnerships, 20, 37

Patent cliffs, 15

Pathways of progress, 167

Patience, 68, 207

Peer coaching, 96, 123, 179

Peer learning, 123, 179, 214–217

Peer reviews, 117

Perception scanning, 37

Performance check-ins, 25–26, 92, 235

Performance reviews, transforming, 117

Perseverance, 203

Personalization at scale, 83

Phenomenology, 132

Pike’s Peak or Bust methodology, 52

Pipeline management, 122–125

aligning initiatives to, 122–123

monitoring progress through, 123

Pipelines:

building and evolving, 130

monitoring progress in, 123–124

structure of, 135f

Pivoting, 130, 200–201

Plan-do-check-act cycle, 112, 115

Planning:

dynamic, 14, 298

static, 296–298

vs. execution, 5

Progress tracking, 25

Problem solving:

collective, 42, 127, 129–136

teams in, 33–34

types of, 41f

Process adherence avoidance, 35

Process definition matrix, 143–145

Process thinker persona, 209

Productivity, redefining, 89

Progress tracking, 25, 94

Purpose:

clarity of, 121-122

driving with, 159–166

Quality metrics, 104–105

Quality movement, founding fathers of, 112

Radical thinking, 130, 208

Randomness generators, 134–135

Re:wire newsletter, ix, 189, 303

Recognition, 104, 117, 215–217

Regulation changes, coping with, 86, 88

Reinforcement learning, 276–277

Relationship building, 164

Remote work, 16

Renewal cycles, 76, 90, 93–95

Responsibility spheres, 18-21

Review phase of problem solving, 41

Rewards:

aligning with purpose, 104-105

non-monetary, 215–217

RFID technology, 23

Ritual, xii, 303

Safe environments, creating, 42

Salesforce, 23, 210–211

Samsung, 17

SAS Institute, 18

Scenario planning, 158

Self-organization, 17–18, 20

Self-reflection, 79, 202

Sensemaking, 161

Sensing systems, digital, 176

70/30 rule, 108

Shadow work, 202

Sharing behavior, 82

Short cycles, 68–69, 254

Silicon Valley Bank, 21

Simon, Herbert, 164

Siemens, 21

Skunk Works program, 101–102

Slack, 21, 23, 82, 127

Smartphones, 87

Social listening, 82

Social media tribes, 82

Sony, 201

Southwest Airlines, 101–102, 203

Specialization, over-, 15

Speed of change, coping with increasing, 13, 86, 199–200

Sponsors, securing alignment from, 59–60

Sprint reviews, 124

Stability avoidance, 36

Staffing challenges, 88–89

Stage-gate process, 143–145

Startups, 21

Strategic initiatives:

calibrating, 301–303

defined, 121–122, 159

driving with purpose, 159–166

harmonizing, 164–166

management of, 122–126

Strategic planning:

dynamic vs. static, 296–298

living, 158

moving from rigid to agile, 296–299

Strategy canvas, 160f

Stress management, 79, 205–206

Structure, importance of flexible, 17–21

Success metrics, defining measurable, 103–105

Suggestion programs, 39

Tactical execution, focusing on, 298

Takeaways phase, 119–120

Teams:

building aligned, 33

creative problem solving by, 33–34

defining objectives, 120–121

diversity’s impact on, 125–127

forming stage of, 125

future of, 16

keys to

• Socializing conclusions involves sharing conclusions from brainstorming/exploration sessions with a wider group to get input and buy-in. Voting can then be used to prioritize conclusions.

• Deep dives at Amazon involve detailed explorations of topics to better understand them. Amazon pioneered e-books and self-publishing.

• The 2-pizza team rule refers to keeping working teams small enough that they can be fed with 2 pizzas.

• Amazon uses narratives and storytelling in their communications and decision making processes.

• Apple pioneered technologies like Apple Pay and the Apple Watch. Fasihuddin details his involvement in launching Apple Pay in various countries.

• Initiatives can be additions to broader workflows/pipelines. They are elements of key focus areas or “pillars.” Proper calibration is important. AI can be used to inform initiatives through analytics and strategic planning.

• Exploration involves researching topics through brainstorms, canvases, and deep dives to better understand problems and possible solutions before making decisions. FAQs are used to socialize conclusions from exploration.

• Working teams are involved in the input, exploration, conclusion, and decision making processes. Their composition and how they interact with executives is important.

Here is a summary of key points about input meetings from the passage:

• Input meetings involve collecting inputs and ideas from teams to help initiate explorations, brainstorm solutions, prepare content, and make decisions. They are contrasted with output meetings which focus on outcomes.

• Inputs can come from working teams, project administrators, C-level executives, and AI/analytics tools. They are a critical element of the overall workflow and transformation process.

• Different types of input meetings include brainstorming sessions, planning meetings, and decision meetings.

• Brainstorming sessions help generate ideas and solutions without judgement. Planning meetings involve defining problems and milestones. Decision meetings identify key choices that need to be made.

• Effective input meetings involve clarifying questions, preparing problem statements, sourcing matters for exploration, and reviewing canvasses or documents to prepare outputs.

• The inputs collected help initiate exploration of new matters, draw conclusions, prepare content packages, and identify decisions that need to be made. They are an important part of project reviews, strategy sessions, and achieving organizational alignment.

• Getting the right inputs from a variety of sources is important for transformation, but too much focus on inputs alone without outputs can also be problematic. Balancing the two is important.

Here is a summary of the key points about the author Atif Rafiq:

• Blazed trails in Silicon Valley and Fortune 500 for over 25 years, holding C-level roles including CDO at McDonald’s and Volvo and President at MGM Resorts.

• Pioneering role as first Chief Digital Officer in Fortune 500 history at McDonald’s, leading one of the largest digital transformations.

• 17-year career in tech companies including GM roles at Amazon, Yahoo!, AOL. Co-founded venture-backed startup Covigna at age 27.

• Holds MBA from University of Chicago and bachelor’s in mathematics-economics from Wesleyan University.

• Built large following as management thinker on LinkedIn and through Re:wire newsletter.

• Advised and invested in over 30 startups, currently sits on boards of Flutter and Clearcover.

• Speaks at top conferences on topics like leadership, innovation, and the future of work. Works to help companies push boldly into the future through his software company Ritual and advisory work.