Tag Archives: Implementation

Top 10 Human-Centered Change & Innovation Articles of August 2022

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Top 10 Human-Centered Change & Innovation Articles of August 2022Drum roll please…

At the beginning of each month we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are August’s ten most popular innovation posts:

  1. Why Amazon Wants to Sell You Robots — by Shep Hyken

  2. Now is the Time to Design Cost Out of Our Products — by Mike Shipulski

  3. How Consensus Kills Innovation — by Greg Satell

  4. The Four Secrets of Innovation Implementation — by Shilpi Kumar

  5. Reset and Reconnect in a Chaotic World — by Janet Sernack

  6. This 9-Box Grid Can Help Grow Your Best Future Talent — by Soren Kaplan

  7. ‘Fail Fast’ is BS. Do This Instead — by Robyn Bolton

  8. The Power of Stopping — by Mike Shipulski

  9. The Battle Against the Half-Life of Learning — by Douglas Ferguson

  10. The Phoenix Checklist – Strategies for Innovation and Regeneration — by Teresa Spangler

BONUS – Here are five more strong articles published in July that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last two years:

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Overcoming Challenges in AI Implementation

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A Human-Centered Approach

Overcoming Challenges in AI Implementation

GUEST POST from Chateau G Pato

Artificial Intelligence (AI) is no longer a futuristic concept; it’s a present-day reality rapidly transforming industries and redefining how we work. Organizations globally are investing heavily, eager to unlock efficiencies, derive unprecedented insights, and carve out significant competitive advantages. Yet, as a human-centered change and innovation thought leader, I frequently observe a disconnect between this enormous potential and the actual success rate of AI initiatives. The most common stumbling blocks aren’t purely technical—they are deeply rooted in human factors and organizational dynamics. To truly harness AI’s power, we must adopt a human-centered implementation strategy, proactively addressing these challenges by putting people at the heart of our efforts.

The Data Foundation: Quality, Access, and Ethical Considerations

The bedrock of any robust AI system is data. Without high-quality, relevant, and accessible data, even the most sophisticated algorithms will falter. Many organizations grapple with data that is inconsistent, incomplete, or siloed across disparate systems, making it a monumental task to prepare for AI consumption. Beyond sheer quality and accessibility, the critical challenge of data bias looms large. AI models learn from historical data, which often reflects existing societal inequalities and prejudices. If left unaddressed, these biases can be perpetuated or even amplified by AI, leading to discriminatory or unfair outcomes. Overcoming this requires robust data governance frameworks, meticulous data cleansing processes, and proactive strategies for bias detection and mitigation from the outset, alongside transparent data lineage.

“AI models are only as good as the data they’re trained on. The critical challenge of data bias looms large, requiring proactive detection and mitigation.”

Bridging the Talent and Understanding Gap

Despite the undeniable demand for AI, a significant skills shortage persists. Organizations often lack the in-house talent—from data scientists and machine learning engineers to AI architects—required for effective development and deployment. However, the talent gap extends beyond technical roles. There’s a crucial need for AI literacy across the entire organization: business leaders who can identify strategic AI opportunities, project managers who can navigate the unique complexities of AI projects, and, critically, front-line employees who will interact with AI tools daily. Without a foundational understanding of what AI is (and isn’t), how it functions, and its ethical implications, fear, resistance, and misuse can undermine even the most promising initiatives. Investment in upskilling and reskilling is paramount.

Navigating Organizational Culture and Resistance to Change

Perhaps the most potent barrier to successful AI implementation is cultural. Humans are inherently wired for comfort with the familiar, and AI often represents a profound disruption to established workflows, roles, and decision-making processes. Common anxieties include fear of job displacement, skepticism about the reliability of “black box” algorithms, and general discomfort with the unknown. Successfully integrating AI demands exceptional change management. This includes transparent communication that clearly articulates AI’s value proposition for individual employees (focusing on augmentation, not just automation), opportunities for involvement in the design and testing phases, and a commitment to continuous learning and adaptation. A culture that embraces experimentation and views AI as a collaborative partner will thrive.

Case Study 1: Healthcare Provider’s Diagnostic AI Transformation

A prominent healthcare system embarked on integrating an AI-powered diagnostic tool designed to assist radiologists in detecting subtle abnormalities in medical images, aiming for earlier disease identification. Initial adoption was sluggish. Radiologists voiced concerns about the AI’s accuracy, fearing it would erode their professional expertise, and found its integration with their existing, disparate PACS (Picture Archiving and Communication Systems) cumbersome. Moreover, the vast imaging data was fragmented and inconsistently labeled across various hospital sites.

The organization responded with a comprehensive, human-centered strategy. They actively involved radiologists in the AI’s development, allowing them to provide direct feedback on model outputs and co-design an intuitive user interface. A critical “explainable AI” component was integrated, enabling radiologists to understand the AI’s rationale for its suggestions, thereby building trust. Data quality was significantly enhanced through a centralized data lake initiative and dedicated teams focused on standardizing imaging protocols. Crucially, the AI was positioned as an “intelligent assistant” augmenting human capabilities, highlighting potential anomalies to allow radiologists to focus on complex cases, leading to improved diagnostic speed and accuracy. Pilot programs with respected, early-adopter radiologists cultivated internal champions, paving the way for widespread acceptance and ultimately, enhanced patient outcomes.

Key Takeaway: Direct user involvement, explainable AI, and framing AI as an augmentation tool are crucial for overcoming professional skepticism and driving adoption in complex domains.

Addressing Ethical Considerations and Robust Governance

As AI becomes increasingly embedded in critical decisions, ethical considerations move from theoretical discussions to practical imperatives. Issues such as algorithmic bias, data privacy, the “black box” problem (lack of transparency), and clear accountability for AI-driven decisions are not optional; they carry significant real-world consequences. Without well-defined governance frameworks, clear ethical guidelines, and robust oversight mechanisms, organizations risk severe reputational damage, hefty regulatory fines (e.g., GDPR violations), and a profound loss of public trust. Building trustworthy AI requires not only proactive ethical design but also explainability features, continuous monitoring for unintended biases, and establishing clear lines of accountability for the performance and impact of AI systems throughout their lifecycle.

Integration Complexity and Scalability Challenges

Moving AI from a proof-of-concept to a scalable, production-ready solution is often fraught with technical complexities. New AI tools frequently encounter friction when integrating with existing, often outdated, and fragmented legacy IT infrastructures. Incompatible data formats, absent or poorly documented APIs, and insufficient computational resources can create significant bottlenecks. Realizing enterprise-wide AI value demands a clear architectural vision, strong engineering capabilities, and a phased, iterative deployment approach that prioritizes interoperability and future scalability. The goal is to avoid isolated “AI islands” and foster a connected, intelligent ecosystem.

Case Study 2: Global Retailer’s AI-Powered Personalization Engine

A leading global retailer aimed to deploy an AI-driven personalization engine for its e-commerce platform, seeking to deliver hyper-relevant product recommendations and targeted promotions. They faced two primary obstacles: customer data was scattered across disparate systems (CRM, loyalty programs, online Browse histories), and skepticism among marketing teams about the AI’s ability to genuinely understand customer preferences beyond simple, rule-based systems.

The retailer strategically addressed data fragmentation by building a unified customer data platform (CDP). Leveraging cloud technologies, they aggregated and meticulously cleansed information from all sources, creating a holistic customer view. To win over the marketing department, they conducted rigorous A/B tests, directly comparing AI-driven personalization against traditional segmentation strategies. The tangible results—a significant uplift in conversion rates and average order value—were undeniable. Furthermore, they provided user-friendly dashboards that offered clear explanations for AI recommendations (e.g., “Customer X purchased Y and viewed Z, similar to other customers who showed interest in this category”). This transparency fostered confidence. By focusing on measurable business outcomes and demonstrating how the AI augmented, rather than replaced, the marketers’ strategic roles, the system gained widespread adoption, becoming a cornerstone of their digital strategy and driving substantial revenue growth.

Key Takeaway: Unifying fragmented data, proving tangible ROI through A/B testing, and providing transparency into AI’s reasoning are vital for securing buy-in and driving adoption of customer-facing AI.

Lack of Strategic Vision and Measurable ROI

A common pitfall is initiating AI projects as isolated experiments without a clear strategic vision or a well-defined business problem to solve. This often leads to “pilot purgatory,” where promising prototypes fail to transition to production, or deployed solutions struggle to demonstrate tangible return on investment (ROI). Successful AI implementation begins with a clear understanding of the specific business challenge, a measurable definition of success, and a robust framework for tracking and communicating the value created. It’s not about implementing AI for AI’s sake, but about leveraging it to achieve meaningful business objectives.

Conclusion: The Human Imperative for AI Success

AI’s transformative potential is immense, but its realization hinges on more than just cutting-edge algorithms and powerful computing. It demands a holistic, human-centered approach that meticulously addresses the intricate interplay of data, talent, culture, ethics, and infrastructure. By prioritizing data quality and ethical governance, investing in comprehensive AI literacy and continuous upskilling, fostering a culture of curiosity, collaboration, and psychological safety, designing AI for human augmentation, and rigorously aligning AI initiatives with clear, measurable business outcomes, organizations can deftly navigate these complex challenges. The future of successful AI implementation lies not solely in technological prowess, but profoundly in our ability to prepare, empower, and integrate the humans who will architect, utilize, and ultimately benefit from this powerful technological revolution.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

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How Design Thinking Drives Successful Product Innovation

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From Ideation to Implementation

How Design Thinking Drives Successful Product Innovation

GUEST POST from Chateau G Pato

In today’s fast-paced and highly competitive marketplace, successful product innovation has become more critical than ever before. Companies that can effectively identify customer needs and transform them into innovative products have a distinct advantage. Design thinking, a human-centered approach to problem-solving, has emerged as a powerful framework to drive product innovation. By cultivating empathy, promoting creativity, and embracing iteration, design thinking enables companies to bridge the gap between customer expectations and product development. In this thought leadership article, we will explore how two different companies, XYZ Inc. and ABC Corp., leveraged design thinking to achieve remarkable success in their product innovation endeavors.

Case Study 1: XYZ Inc. – Transforming Healthcare Solutions

XYZ Inc., a leading healthcare technology company, sought to develop a user-friendly and accessible patient monitoring system. They understood that the existing solutions lacked personalization and failed to account for the emotional aspect of patient interactions. To overcome these challenges, XYZ Inc. adopted design thinking methodologies.

Empathy-driven research: The XYZ Inc. began by conducting in-depth interviews with healthcare professionals, patients, and their families to understand their pain points and needs. By actively listening and observing, the design team gained valuable insights into the emotional and physical experiences associated with patient monitoring.

Ideation and prototyping: Armed with empathy-driven research, the design team enthusiastically engaged in ideation sessions. They generated a range of ideas, keeping the end-users’ motivations and goals at the forefront. Prototypes were swiftly developed, allowing for early-stage feedback and iterative improvements.

User testing and iteration: XYZ Inc. conducted extensive user testing to validate their prototypes. Real-time feedback from healthcare professionals and patients allowed them to refine their product, incorporating improvements that directly addressed their users’ needs. This iterative process repeated until XYZ Inc. had a highly intuitive, patient-centric monitoring system ready for implementation.

Implementation and impact: The final product was met with widespread acclaim within the healthcare community. The integration of design thinking principles resulted in a solution that significantly reduced nurses’ burden, increased patient satisfaction, and improved the overall quality of care. XYZ Inc. is now considered a pioneer in the field, with their design thinking approach becoming an industry benchmark.

Case Study 2: ABC Corp. – Revolutionizing Retail Experience

ABC Corp., a renowned retail brand, realized the need to enhance their customers’ in-store experience. They aimed to create a seamless and personalized journey to increase engagement and encourage repeat purchases. Applying design thinking principles allowed ABC Corp. to reimagine the retail experience, resulting in substantial improvements.

Empathic understanding of customer needs: ABC Corp. embarked on an extensive research phase by shadowing customers, conducting interviews, and hosting focus groups. This research helped them uncover pain points, frustrations, and desires of shoppers, allowing the design team to delve deeper and empathize with their customers.

Ideation and co-creation: Armed with customer insights, multi-disciplinary teams at ABC Corp. engaged in collaborative brainstorming sessions. They fostered a culture of inclusive ideation, involving employees from different departments, including store associates, marketing, and technology experts, to ensure a comprehensive approach. This collaborative environment enabled the generation of transformative ideas.

Rapid prototyping and testing: ABC Corp. built quick prototypes and conducted mock store simulations to evaluate the feasibility and effectiveness of new concepts. By observing customer interactions and gathering feedback, they iteratively refined their ideas, ensuring that the final product aligned closely with customer needs and preferences.

Implementation and impact: ABC Corp. successfully implemented their new retail experience across their stores, incorporating personalized recommendations, interactive displays, and an improved checkout process. The customer response was overwhelmingly positive, leading to a significant increase in sales, customer loyalty, and brand advocacy. ABC Corp. became a leader in this innovative approach to retail, inspiring competitors to follow suit.

Conclusion

The two case studies of XYZ Inc. and ABC Corp. demonstrate how design thinking drives successful product innovation by incorporating empathy, creativity, and iterative problem-solving. By focusing on the end-users’ needs, these companies identified valuable insights that had a profound impact on their product development and implementation. Through design thinking, XYZ Inc. transformed patient monitoring, while ABC Corp. elevated the retail experience. Both companies achieved remarkable success and emerged as leaders in their respective industries. Embracing design thinking principles empowers organizations to bridge the gap between ideation and implementation, leading to products that truly resonate with customers and drive unparalleled growth.

SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.

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How to Close the Sickcare AI DI Divide

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How to Close the Sickcare AI DI Divide

GUEST POST from Arlen Meyers

The digital divide describes those having or not having access to broadband, hardware, software and technology support. It’s long been acknowledged that even as the digital industry exploded out of this country, America lived with a “digital divide.” While this is loosely understood as the gap between those who have access to reliable internet service and those who don’t, the true nature and extent of the divide is often under-appreciated. Internet infrastructure is, of course, an essential element of the divide, but infrastructure alone does not necessarily translate into adoption and beneficial use. Local and national institutions, affordability and access, and the digital proficiency of users, all play significant roles — and there are wide variations across the United States along each of these.

There is also a sickcare artificial intelligence (AI) dissemination and implementation (DI) divide. Infrastucture is one of many barriers.

As with most things American, there are the haves and the have nots. Here’s how hospitals are categorized. Generally, the smaller ones lack the resources to implement sickcare AI, particularly rural hospitals which are, increasingly, under stress and closing.

So, how do we close the AI-DI divide? Multisystems solutions involve:

  1. Data interoperability
  2. Federated learning Instead of bring Mohamed to the mountain, bring the mountain to Mohamed
  3. AI as a service
  4. Better data literacy
  5. IT infrastructure access improvement
  6. Making cheaper AI products
  7. Incorporating AI into a digital health whole product solution
  8. Close the doctor-data scientist divide
  9. Democratize data and AI
  10. Create business model competition for data by empowering patient data entrepreneurs
  11. Teach hospital and practice administrators how to make value based AI vendor purchasing decisions
  12. Encourage physician intrapreneurship and avoid the landmines
  13. Use no-code or low-code tools to innovate

We are still in the early stages of realizing the full potential of sickcare artificial intelligence. However, if we don’t close the AI-DI gaps, a large percentage of patients will never realize the benefits.

Image Credit: Pixabay

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Implementing Design Thinking in Your Organization

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Implementing Design Thinking in Your Organization

GUEST POST from Chateau G Pato

Design Thinking is a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success. It’s a mindset that helps organizations to think more creatively and to behave in a more user-centric way. Below, we explore two case studies that demonstrate the successful implementation of Design Thinking in organizations.

Case Study 1: The Guardian Newspaper

The Challenge: The Guardian faced the challenge of adapting to the digital age, needing to change their funding model, boost revenue, and engage with their readers on an emotional level.

The Design Thinking Approach: The Guardian implemented Design Thinking to overhaul their approach to reader engagement and revenue generation. They focused on understanding their readers’ needs and desires, which led to the development of new user-centric products and services.

The Outcome: By applying Design Thinking, The Guardian was able to create a more sustainable business model. They increased reader engagement and revenue by introducing new digital products that were closely aligned with their readers’ expectations¹.

Case Study 2: Lummi Tribal Clinic – Tackling the Opioid Crisis

The Challenge: The Lummi Tribal clinic was grappling with the devastating effects of the opioid crisis on its community.

The Design Thinking Approach: The clinic used Design Thinking to address the crisis at both human and systemic levels. They empathized with affected individuals to understand the root causes and developed solutions that were culturally sensitive and community-focused.

The Outcome: The clinic’s Design Thinking approach led to the creation of programs that significantly reduced opioid overdoses in the community. Their solutions were not only effective but also respectful of the community’s cultural values¹.

Conclusion

Design Thinking is not just a process; it’s a way of thinking that can transform organizations. It encourages empathy, fosters creativity, and drives innovation. As seen in the case studies of The Guardian and the Lummi Tribal clinic, Design Thinking can lead to profound changes in organizational culture and outcomes. It’s a powerful tool for any organization looking to stay relevant and responsive in today’s fast-paced world.

For those interested in exploring more about Design Thinking and its impact, the Design Thinking Association offers a wealth of resources and case studies that delve deeper into this transformative approach¹.

References:
(1) Explore: Design Thinking Case Studies | The Design Thinking Association. https://www.design-thinking-association.org/explore-design-thinking-topics/design-thinking-case-studies.
(2) Explore 10 Great Design Thinking Case studies – The Knowledge Academy. https://www.theknowledgeacademy.com/blog/design-thinking-case-study/.
(3) Implementing Design Thinking: Understanding Organizational Conditions …. https://cmr.berkeley.edu/2020/02/62-2-wrigley/.
(4) Can Design Thinking Succeed in Your Organization?. https://sloanreview.mit.edu/article/can-design-thinking-succeed-in-your-organization/.
(5) Implementing Design Thinking: Understanding Organizational Conditions …. https://hbsp.harvard.edu/product/CMR729-PDF-ENG.

SPECIAL BONUS: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

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Design Thinking Across Industries

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How to Implement It in Your Workplace

Design Thinking Across Industries

GUEST POST from Chateau G Pato

Design thinking is a problem-solving approach that has garnered significant attention in recent years. Originally embraced by the design industry, it has now expanded its influence across a wide range of sectors, from technology and healthcare to finance and education. This article will explore how design thinking can be successfully implemented in various industries through the analysis of two case studies.

Case Study 1 – Airbnb: Transforming the Hospitality Industry

One prominent example of design thinking in action is Airbnb, the online marketplace for short-term rentals. In the early stages of their journey, Airbnb encountered a major challenge: the lack of trust between hosts and guests. To address this issue, the company applied design thinking principles to reimagine the user experience and build a platform centered around trust and community.

Airbnb identified that photographs played a crucial role in establishing trust. They started by sending professional photographers to capture appealing images of listed properties. This step not only improved the overall quality of the platform but also helped to foster trust between hosts and guests. Additionally, Airbnb introduced a review system, enabling users to provide feedback and ratings for both hosts and guests. This feedback mechanism helped further build trust and accountability within the community.

By adopting a design thinking approach, Airbnb was able to create an innovative solution to a common industry problem. They focused on human-centered design, empathy, and iterative prototyping, leveraging these principles to revolutionize the hospitality industry.

Case Study 2 – Kaiser Permanente: Enhancing Healthcare Services

Design thinking has also been successfully applied in the healthcare sector, as demonstrated by the renowned healthcare organization, Kaiser Permanente. Their goal was to improve the patient experience by reducing wait times and enhancing communication between patients and medical staff.

To achieve this, Kaiser Permanente undertook a redesign of their emergency departments, seeking to understand the pain points and barriers experienced by patients. They engaged in empathy research, observing and interviewing patients to gain a deeper understanding of their needs and frustrations.

Based on these insights, Kaiser Permanente implemented various design-driven solutions. They simplified and clarified signage to reduce confusion, created digital tools to provide patients with real-time updates on their wait times, and introduced a triage system to prioritize patients based on the severity of their condition. These changes not only improved the overall patient experience but also optimized the workflow of medical professionals, resulting in more efficient and effective care.

By utilizing design thinking principles, Kaiser Permanente transformed their healthcare services, making them more patient-centric and responsive to individual needs.

Implementing Design Thinking in Your Workplace

To introduce design thinking in your workplace, consider the following steps:

1. Foster a culture of innovation: Encourage your team to think creatively and embrace a problem-solving mindset. Provide a safe space for experimenting and taking risks.

2. Empathize with users: Understand the needs, desires, and pain points of your target audience. Engage in research and direct observation to gain empathy and develop a deeper understanding of their experiences.

3. Prototype and iterate: Develop prototypes and continually refine your solutions based on feedback and testing. Embrace an iterative process that allows for continuous improvement.

4. Collaborate and seek diverse perspectives: Design thinking thrives on collaboration and diverse viewpoints. Encourage cross-functional teams and create opportunities for brainstorming and sharing ideas.

5. Embrace failure as a learning opportunity: Design thinking often involves trial and error. Embrace failure as a stepping stone to success and encourage a culture of continuous learning and growth.

By implementing design thinking principles, organizations can drive innovation, improve their products and services, and create meaningful user experiences. By learning from successful cases, such as Airbnb and Kaiser Permanente, businesses across industries can benefit from this problem-solving approach and stay ahead in an ever-evolving market.

EDITOR’S NOTE: Braden Kelley’s Problem Finding Canvas can be a super useful starting point for doing design thinking or human-centered design.

“The Problem Finding Canvas should help you investigate a handful of areas to explore, choose the one most important to you, extract all of the potential challenges and opportunities and choose one to prioritize.”

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How to Successfully Implement a Digital Transformation Strategy

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How to Successfully Implement a Digital Transformation Strategy

GUEST POST from Art Inteligencia

Digital transformation is becoming increasingly important for businesses in the modern economy. Companies must adopt new technologies and strategies in order to stay competitive and remain relevant in the market. Implementing a successful digital transformation strategy is critical to achieving success in the digital world.

STEP ONE: Assess Your Capabilities

The first step to implementing a successful digital transformation strategy is to assess the capabilities of the company. This evaluation should include an analysis of current technology, processes, and systems. Companies should also look at their customer base and the competitive landscape. This assessment will help the company identify areas for improvement and determine the best course of action for digital transformation.

STEP TWO: Define the Objectives

Once the assessment is complete, the next step is to define the objectives of the digital transformation. Companies should consider their current capabilities and the desired outcomes that they want to achieve. This will help them create a clear roadmap for the transformation process.

STEP THREE: Develop a Plan

The next step is to develop a plan for implementing the digital transformation. This plan should include a timeline, budget, and resources needed to complete the project. Companies should also consider the risks associated with the transformation and develop a strategy to mitigate them.

STEP FOUR: Create an Agile Environment

Once the plan is in place, the next step is to begin implementing the digital transformation. Companies should focus on creating an agile environment that is willing to take calculated risks and experiment. This is essential for successful digital transformation because it allows the company to quickly identify and address any issues that might arise.

STEP FIVE: Measure the Success

Finally, companies should measure the success of the digital transformation. Companies should track key metrics such as customer satisfaction, cost savings, and efficiency to assess the impact of the transformation. This will help the company adjust its strategy if needed and ensure that it is achieving the desired outcomes.

Implementing a successful digital transformation strategy is essential for companies in the modern economy. By assessing their current capabilities, defining objectives, developing a plan, and measuring success, companies can ensure that their digital transformation is successful.

The Human-Centered Change methodology leverages more than 70 tools and is a great way to plan a digital transformation.

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Change Management: A Leader’s Guide to Effective Implementation

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Change Management: A Leader's Guide to Effective Implementation

GUEST POST from Chateau G Pato

Change is a natural part of life, and so businesses must learn to make timely adjustments to stay competitive and successful in the long-term. As a leader, it is your responsibility to ensure that change is properly implemented and managed so that you and your organization are placing strategic efforts where needed. This article serves as a guide to help business leaders implement effective change management strategies in their organization.

What is Change Management?

Change management is a structured process of organizing and controlling a company’s adjustment efforts. It is considered the cornerstone of large-scale transformation and is executed with the general idea of limiting risks and maximizing the potential of positive outcomes from change initiatives. It includes four core components: analysis, planning, implementation, and review. Through these four components, organizations can strategically transform their operations, core systems, and approaches to mission-critical processes.

Why is Change Management Important?

Change management is important because it helps organizations respond to their changing environments efficiently and effectively. It serves as a system of checks and balances and ensures that all change initiatives are properly justified, planned, and implemented. The process also helps businesses minimize the waste of resources and ensure that teams involved in various projects are best working towards the same goal.

Case Study 1 – The Transformation of Microsoft

Microsoft launched an extensive internal transformation project in 2014 to update its core operations, systems, and approaches. This involved a massive overhaul of the company’s internal processes, such as switching to an agile development method. Microsoft implemented a comprehensive change management approach, which included extensive training, workforce planning, and organizational realignment initiatives. The transition was a success and enabled Microsoft to remain a leader in their industry.

Case Study 2 – The Reorganization of National Grid

National Grid, a major electric and gas utility provider, restructured its organization to meet new customer demands and market trends. The company implemented a state-of-the-art change management system to execute the reorganization process across all departments and subsets of the company. This involved a rigorous assessment process, strategic workforce planning, detailed metrics, and advanced decision-making methods. The reorganization successfully enabled National Grid to better respond to changes in its environment and remain competitive in the industry.

Conclusion

Effective change management helps organizations respond to changes in their industry and remain competitive in the long-term. As a leader, it is important to understand the various components of change management and ensure that initiatives are properly planned and implemented. By considering the two case studies provided in this guide, business leaders can gain invaluable insight into the tools and processes that can help their organization successfully manage change.

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How to Integrate Design Thinking into Your Organization

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How to Integrate Design Thinking into Your Organization

GUEST POST from Art Inteligencia

Design thinking is a powerful and innovative approach to problem solving that has become essential in many industries. It is a process of creative problem solving that starts with understanding the user’s needs and then working with them to come up with creative solutions. Design thinking has been adopted by many organizations and can be used to develop innovative and user-friendly products, services, and experiences. The following article will explore how to integrate design thinking into your organization and the five benefits that it can bring.

Integrating design thinking into your organization is a great way to foster a culture of creativity and innovation. Here are some tips on how to do it:

1. Begin by introducing design thinking to your team

Start by introducing the concepts of design thinking and user-centered design to your team. Explain the basics of the approach and how it can be applied to different projects. Show them examples of successful applications and allow them to ask questions. This will give them a better understanding of the process and help them to see the value of incorporating design thinking into their work.

2. Create a space for experimentation and collaboration

Design thinking relies on collaboration and experimentation to come up with innovative solutions. Create a collaborative environment in your organization that encourages employees to explore different ideas and approaches. Make sure everyone has access to the necessary tools, such as design software or prototyping materials. Provide ample time for your team to explore and experiment with new ideas.

3. Foster a culture of innovation

Encourage your team to think outside the box and come up with creative solutions. Reward employees for coming up with innovative ideas and encourage them to take risks. Provide resources and support to help them find new ways to solve problems.

4. Revisit and revise

Design thinking is an iterative process. Revisit your designs and products on a regular basis and make changes as needed. Listen to feedback from users and incorporate their insights into your design process. This will help you create better products and services that meet user needs.

Five Benefits of Integrating Design Thinking into Your Organization

Integrating design thinking into your organization can help you create better products and services and improve your overall operations. By introducing the concept to your team, creating a space for experimentation and collaboration, fostering a culture of innovation, and revisiting and revising your designs regularly, you can start to reap the benefits of design thinking in your organization.

1. Improves Problem Solving: Design thinking is an effective way to solve complex problems and come up with innovative solutions. By looking at problems from a user’s perspective, you can identify the underlying issues and develop solutions that are tailored to the specific needs of the user. This approach helps organizations to create better products, services, and experiences that meet the needs of their customers and stakeholders.

2. Increases Collaboration: Design thinking encourages collaboration among employees, customers, and other stakeholders. Working together allows for a greater exchange of ideas and a better understanding of the user’s needs. This can lead to more creative and effective solutions.

3. Fosters Creative Thinking: Design thinking encourages creative thinking and out-of-the-box solutions. By looking at problems from different angles, it is easier to come up with creative solutions that are tailored to the user’s needs.

4. Enhances User Experience: Design thinking helps to ensure that products, services, and experiences are designed with the user in mind. By understanding the user’s needs and creating solutions that are tailored to the user, it is possible to create a more engaging and satisfying user experience.

5. Improves Efficiency: Design thinking can help to streamline processes and make them more efficient. By understanding the user’s needs and creating solutions that are tailored to the user, it is possible to make processes more efficient and reduce waste.

Integrating design thinking into your organization can bring many benefits, but it is important to ensure that it is implemented correctly. It is also important to ensure that employees are trained in the process and that it is used consistently throughout the organization. By doing this, you can ensure that you are able to reap the rewards of design thinking and create better products, services, and experiences for your users.

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Transform Your Business with a Change Success Manager

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Transform Your Business with a Change Success Manager

“Stealing the role of customer success manager from the world of SaaS is the key to making your digital transformation efforts a success.”

I was speaking with a headhunter recently about some of the roles she was recruiting for and there was one that captured my attention. It was a posting she had for a customer success manager at one of your favorite three letter software companies. And, as she extolled the merits of the role I found myself thinking that the management practice of organizational change is still so immature. There are still so many missing tools and mindsets in the organizational behavior area of management science.

What I found so captivating about the responsibilities of a customer success manager, is that the kinds of tasks she described are exactly the kinds of activities that need to be performed as part of any organizational change effort. The difference is that software companies have recognized that they need to have people dedicated, ideally from the very beginning of the process, to help connect the cross-functional dots for the customer behind the scenes, actively manage expectations and outcomes, ensure a mutual understanding of what success looks like, and to make sure that it is ultimately achieved.

Technology companies everywhere seem to be racing to embrace the role of customer success manager as a new member of their army of service professionals. And, the customer success manager, above all else, strives to ensure that every customer moves beyond purchase, beyond installation, beyond first use, to productive use, deepening engagement, and the holy grail of retention and referral.

And retention is key in SaaS businesses because the churn rate (13% per year on adverage) is higher than other subscription type businesses (6-8% per year according to Recurly Research), but lower than the churn rate for some wireless carriers (which averages between 1-3% per month). Churn rate is a statistic measuring those customers who choose not to renew their service, or to switch their service to another subscription provider. A churned customer doesn’t write you a check for next year, or future years either.

The main reason SaaS customers churn, especially after their first year, is that the perceived value of the subscription is insufficient relative to the price to justify renewing it. They may have bought the software but didn’t install it, installed it but never really got up and running with it, or just found it too hard to get the value out of the software that they were promised. The old technology sales model didn’t care about these situations. Tech companies just focused on closing the sale, recognizing the revenue and moving on to close the next prospect. With the SaaS model, sales are no longer king, adoption and engagement are king. If the customer doesn’t adopt, engage and expand their footprint with your SaaS offering then it is easy for them to switch to an offering of a competitor.

So, if customer success managers are so instrumental to the success of technology companies in the era of the cloud, why shouldn’t they also be considered instrumental inside of our organizations as the key to successful change?

The problem is that too many organizations are still stuck in an upside-down paradigm where change management is seen as a bolt on to project management, instead of truly architecting our organizations for successful change.

Companies that want to be successful over the long term understand that change is not an event but a constant. They strategically select those capabilities and competencies needed for the next phase of their evolution, plan a portfolio of change initiatives that executes upon their strategy, and understand that change saturation and change readiness must always be considered. Companies that succeed in this era of unending change will constantly manage the expectations of their people around each change initiative and how the process will work and what the technology can and can’t do.

It is not surprising that companies would first embrace a role that adds tremendous value on the revenue generating side of the business first. Technology companies have determined customer success managers are critical to helping customer organizations adopt changes imposed by new technologies while ultimately increasing the lifetime value of each new customer. But for similar reasons internal to the organization, companies must also now embrace the need for a role I’d like to call the change success manager.

A change success manager is a change manager on steroids. However, in today’s business climate most people think of a change manager as the person a project manager brings in near the end of a software implementation project that does the training or communications. That may be how companies are doing the so-called people side of change today, but it is wrong!

This new role of change success manager is intended to lead each change initiative inside the organization from beginning to end. A change success manager is brought in at the beginning of the process to reach across the organization and identify a cross functional team specific to the needs of each change initiative for the purposes of convene as part of a change planning workshop. This change planning team will facilitate each change planning workshop using tools like the Change Planning Toolkit™ to identify the change leadership team that will take decisions and remove roadblocks for the change management team that will facilitate the actions necessary to advance the change initiative to its desired outcomes.

And, unlike the current model of change that many organizations follow, a change success manager will have one or more project managers on their change management team to identify the appropriate pace for the project, and the right size for the work packages, in order to maintain momentum across the entire duration of the change initiative and increase the adoption of internal change – just like a customer success manager increases the adoption of external changes!

This article originally appeared on CIO.com


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