Tag: Operations

The Ultimate Guide to Product Operations: Navigating the Emerging Field

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Introduction

Product Operations, often referred to as Product Ops, is a relatively new yet increasingly vital role within technology companies, particularly those experiencing rapid growth. While operations functions like Sales Operations (Sales Ops) and Marketing Operations (Marketing Ops) have been well-established for years, Product Ops is just beginning to gain traction. However, for companies scaling their operations, the presence of a dedicated Product Ops team can be the difference between seamless expansion and significant operational challenges.

This comprehensive guide delves into the role of Product Ops, its importance within an organization, how it functions, and why it is becoming indispensable. We will also explore the different models of Product Ops, its core responsibilities, and how to get started with implementing this function in your organization.

Understanding Product Operations

At its core, Product Ops is the intersection of Product Management, Engineering, and Customer Success. It acts as a bridge, ensuring that these departments are aligned and working together efficiently to support the Research and Development (R&D) team as well as the go-to-market strategies. The role of Product Ops involves streamlining communication, refining processes, and fostering better alignment during the entire product lifecycle—from development to launch and subsequent iterations.

However, the definition and responsibilities of Product Ops can vary significantly depending on the organization. This variation is largely due to the novelty of the role and the specific needs of different teams and businesses. Despite these differences, there are three primary models of Product Ops that have emerged:

  1. Outcomes-driven Model: In this model, Product Ops focuses on gathering insights and scoping out business needs at the very beginning of the product development process. This often involves going out into the field, talking to users, and understanding their needs. Product Ops plays a critical role in launch execution, working closely with operations counterparts globally to ensure that the go-to-market strategy is effective. Uber is a prime example of a company that uses an outcomes-driven approach in its Product Ops function.
  2. Efficiency-focused Model: Here, the primary objective of Product Ops is to deliver more value to users more quickly. This model emphasizes strengthening product feedback loops, operationalizing products, and scaling product knowledge across the organization. Stripe employs this efficiency-focused model, where Product Ops ensures that the product delivers maximum value at the fastest pace possible.
  3. Customer-centric Model: In this model, Product Ops is heavily involved in the customer experience, providing insights that span the entire customer journey through the lens of the product. Theresa Baker’s role at Comcast exemplifies this approach, where Product Ops focuses on understanding and enhancing the end-to-end customer experience for their Digital Home product.

Where Does Product Ops Fit in an Organization?

Product Ops is typically embedded within the Product Management team or positioned in an adjacent function that reports directly to the Head of Product. The role serves as a shared resource across the product management organization, driving initiatives that enhance product efficiency, effectiveness, and alignment with broader business objectives.

The Dual Nature of Product Ops: Role and Skillset

Product Ops is not just a job title; it’s also a critical skill set that can benefit any product professional. Some organizations view Product Ops as a specific role that needs to be filled, while others see it as a capability that should be developed across the entire product team. Ideally, product-led organizations should have a designated Product Ops leader, but they should also encourage all product team members to cultivate an operational mindset.

The demand for Product Ops professionals is on the rise. A search on LinkedIn reveals nearly 5,700 users with the title “Product Operations,” an 8% increase in the last year alone. Even more striking is the 80% year-over-year increase in LinkedIn users listing Product Operations as a skill. This surge indicates that while the role is still evolving, its importance is being increasingly recognized across the industry.

The Growing Importance of Product Ops

Several key factors contribute to the rising prominence of Product Ops:

  1. Heightened Customer Expectations: Today’s customers demand seamless, personalized experiences. Product Ops ensures that the product meets these expectations by optimizing the development process and enhancing the customer experience from trial and purchase through onboarding, expansion, and referrals.
  2. The Proliferation of Operations Roles: The success of other operational roles, such as Sales Ops and Marketing Ops, has paved the way for Product Ops. As companies recognize the value of operations in driving efficiency and effectiveness, they are beginning to apply these principles to product development.
  3. Availability of Product Usage Data: The explosion of data has made it essential for organizations to have dedicated roles focused on analyzing and acting on this information. Product Ops plays a crucial role in turning product usage data into actionable insights that inform decision-making.
  4. Product-Led Growth: Companies that adopt a product-led growth strategy—where the product itself is the primary driver of customer acquisition, retention, and expansion—tend to outperform their peers. These companies are more likely to employ a Product Ops leader or even an entire team to ensure that their product development and go-to-market strategies are optimized for success.

Core Responsibilities of Product Ops

The responsibilities of Product Ops can be broadly categorized into five key areas:

  1. Tools Management: Product Ops is responsible for managing the product team’s tech stack, including tool selection, integration, and maintenance. This role involves overseeing relationships with vendors and ensuring that the tools are used effectively across the organization. Product Ops also establishes best practices for tool usage, ensuring that the team operates efficiently and effectively.
  2. Data Management and Analysis: With the proliferation of tools comes an increase in available data. Product Ops ensures that this data is clean, organized, and easily accessible, providing a strong foundation for data-driven decision-making. Product Ops plays a critical role in collecting, analyzing, and synthesizing data from multiple sources to inform product strategy and improve product outcomes. This includes reconciling usage data with customer feedback, performing data analysis, and providing insights to necessary stakeholders.
  3. Experimentation: One of the key benefits of having a dedicated Product Ops role is the ability to run more experiments with less friction. Product Ops tracks all active experiments, ensuring they do not overlap or interfere with each other. This role also streamlines the sequencing and implementation of experiments, establishing workflows, documentation, and segmentation of user populations to ensure clean and accurate data collection.
  4. Strategy and Cross-Team Collaboration: Product Ops acts as a strategic partner to teams across the organization, driving collaboration around product initiatives. This role involves aligning with teams like Revenue Operations (RevOps), Development Operations (DevOps), Customer Success, Marketing, and Sales to ensure that product data informs broader business decisions. Product Ops also scales product knowledge across the organization, acting as a central resource for product information, new learnings, and roadmap updates.
  5. Trusted Advisor to Leadership: As companies scale, the need for informed decision-making becomes critical. Product Ops serves as a trusted advisor to Chief Product Officers (CPOs), VPs of Product, and other R&D leaders, providing data-driven insights that guide strategic decisions. This role involves advising on the product roadmap, supplying product health data to the executive team, and ensuring that product decisions align with overall business objectives.

The Impact of Product Ops on the Organization

The introduction of a Product Ops function can significantly impact the organization in several ways:

  • Shifts in Ownership: Product Ops takes on many of the administrative and organizational tasks that Product Managers previously handled, allowing them to focus more on product strategy and development. This shift includes gathering and organizing data, running experimentation processes, collecting customer feedback, and training and enabling other teams.
  • Improved Cross-Team Communication: By serving as the product expert for other teams, Product Ops establishes clearer communication channels and ensures that everyone knows where to find the information they need. This improves communication around the product and enhances collaboration across the organization.
  • Increased Efficiency: Better communication leads to greater efficiency. When teams have access to the right information at the right time, they can make decisions more quickly and effectively. Additionally, by relieving Product Managers of operational tasks, Product Ops enables them to build and release products faster.
  • Connecting Product to the Bottom Line: Product Ops helps organizations connect product decisions with their overall business strategy, driving key business objectives and positively impacting the bottom line. For example, at Comcast, the Product Ops team helps identify product enhancements that reduce support calls or technician visits, leading to operational savings.

The Future of Product Ops

As more companies adopt data-driven approaches and recognize the value of product-led growth, the role of Product Ops is expected to continue evolving and growing in importance. The future of Product Ops may involve the merging of different analytical and operational functions, creating a more comprehensive product operations team.

Industry experts predict that the number of tools available for Product Ops will increase, mirroring the maturity of tools in Sales Ops. Additionally, the role may become more strategic, with Product Ops leaders acting as mini Chief Operating Officers (COOs) within product teams.

Getting Started with Product Ops

For organizations looking to implement a Product Ops function, the best approach is to start small and demonstrate results. Begin by identifying a few key areas where Product Ops can add value, such as managing the tech stack, improving data quality, or streamlining experimentation processes. As the function proves its worth, it can be scaled to take on additional responsibilities.

It’s also important to hire or develop the right talent for Product Ops. Successful Product Ops professionals are analytical, comfortable with systems, collaborative, great communicators, entrepreneurial, and have strong business acumen. They should also have a solid understanding of product management and leadership skills, even if they do not have direct reports.

Conclusion

Product Ops is an emerging function that is quickly becoming a cornerstone of successful product-led organizations. As technology companies scale, the need for a dedicated function to manage the complexities of product development, data analysis, and cross-team collaboration becomes increasingly apparent. Product Ops fills this gap, providing the necessary infrastructure to ensure that products are developed efficiently, aligned with customer needs, and contribute to the overall business strategy.

The Long-Term Vision for Product Ops

Looking ahead, the evolution of Product Ops will likely involve deeper integration with other operational roles and a more pronounced influence on strategic decision-making within organizations. Here are some key trends and developments that could shape the future of Product Ops:

  1. Greater Emphasis on Data-Driven Decision Making: As companies continue to accumulate vast amounts of data, the role of Product Ops in synthesizing this information into actionable insights will become even more critical. This will likely lead to the development of more sophisticated data tools and methodologies, enabling Product Ops teams to provide even more granular and impactful recommendations.
  2. Integration with Emerging Technologies: The rise of artificial intelligence (AI) and machine learning (ML) will offer new opportunities for Product Ops to enhance their data analysis capabilities. By leveraging AI and ML, Product Ops can automate routine tasks, identify patterns and trends that may not be immediately apparent, and make more accurate predictions about product performance and customer behavior.
  3. Expansion of the Product Ops Skill Set: As the role of Product Ops expands, so too will the skill set required to succeed in this field. Future Product Ops professionals will need to be well-versed not only in data analysis and product management but also in emerging technologies, customer experience strategies, and advanced project management techniques.
  4. Cross-Functional Leadership: Product Ops is poised to become a key player in cross-functional leadership, bridging the gap between product teams and other departments such as marketing, sales, and customer success. As the role becomes more strategic, Product Ops leaders may find themselves involved in broader organizational decisions, influencing everything from go-to-market strategies to company-wide operational efficiencies.
  5. Product Ops as a Strategic Partner: The evolution of Product Ops into a strategic partner means that this function will not only support product development but also shape the direction of the company’s growth. This shift will require Product Ops teams to develop a deep understanding of the business landscape, competitive dynamics, and customer expectations, allowing them to contribute to high-level strategic planning.
  6. Educational and Professional Development Opportunities: As the importance of Product Ops continues to grow, educational institutions and professional organizations are likely to develop specialized programs and certifications to prepare the next generation of Product Ops leaders. These programs could cover a wide range of topics, from data science and analytics to product strategy and customer experience management.

Getting Started: Building Your Product Ops Function

For organizations considering the implementation of a Product Ops function, here are some practical steps to get started:

  1. Assess Your Current Needs: Begin by evaluating where your current product processes are experiencing friction or inefficiencies. Identify areas where improved alignment, data analysis, or process optimization could have the most significant impact. This assessment will help you determine the specific responsibilities and focus areas for your Product Ops team.
  2. Define the Scope and Structure: Based on your needs assessment, define the scope of your Product Ops function. Will it primarily focus on data management, experimentation, or cross-team collaboration? Consider the structure of the team—will it be a small, centralized group, or will Product Ops professionals be embedded within different product teams?
  3. Start Small and Scale: Start by implementing Product Ops on a small scale, focusing on one or two key areas where you can quickly demonstrate value. As the function proves its worth, you can expand the team’s responsibilities and scale the function across the organization.
  4. Hire or Develop the Right Talent: Look for individuals who possess the core skills needed for Product Ops: strong analytical abilities, comfort with systems, excellent communication skills, and a collaborative mindset. Consider providing training or professional development opportunities to help your team members grow into their roles.
  5. Establish Clear Processes and Best Practices: Develop clear processes and best practices for the Product Ops function. This includes defining workflows for data collection and analysis, setting up tools and systems for experimentation, and creating communication channels between Product Ops and other departments.
  6. Measure and Iterate: Continuously measure the impact of your Product Ops function and be prepared to iterate on your approach. Use key performance indicators (KPIs) such as product delivery predictability, feature adoption rates, and customer satisfaction scores to assess the effectiveness of Product Ops and make data-driven adjustments as needed.

Final Thoughts

The rise of Product Ops represents a significant shift in how technology companies approach product development and operational efficiency. By centralizing and optimizing key processes, Product Ops enables organizations to build better products, respond more effectively to customer needs, and achieve sustainable growth.

As the role of Product Ops continues to evolve, it will undoubtedly become a strategic pillar within the most successful organizations. Those who invest in developing a robust Product Ops function today will be well-positioned to navigate the complexities of tomorrow’s business landscape, ensuring that their products—and their companies—thrive in an increasingly competitive market.

Whether you are just starting to explore Product Ops or looking to refine an existing function, this guide provides the foundational knowledge and actionable insights needed to succeed. Embrace the potential of Product Ops, and watch as it transforms your product team into a powerhouse of efficiency, innovation, and customer satisfaction.

Join the Product Ops Revolution

Ready to elevate your product operations to the next level? Explore the Radical Product Thinking: Vision Setting course today, or request a demo to see how we can help your team achieve operational excellence. Together, we can build great products and drive transformative success in the digital era.

The Perils of Losing Perspective: Why Senior Leaders Must “Stay in the Helicopter” for Strategic Success

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Introduction

Have you ever found yourself so deeply immersed in a hectic period that your operational duties blur the lines of strategic focus? In the fast-paced world of business, senior leadership often faces the challenge of balancing day-to-day operations with long-term strategic planning. This reminded me of a book I’ve read in 2016 – “Staying in the Helicopter: The Key to Sustained Strategic Success,” in which Richard Harrop, uses the metaphor of “staying in the helicopter” to emphasize the importance of maintaining a high-level perspective. This book has been invaluable in helping me understand the importance of maintaining a high-level perspective while managing the complexities of daily operations, ensuring that an organisation remains agile, innovative, and competitive. However, what happens when senior leaders get too involved in the minutiae of daily operations? This blog post explores the risks businesses face when their leaders “get out of the helicopter” and lose sight of the broader strategic picture.

Staying in the Helicopter – maintaining a strategic, high-level perspective

“Staying in the Helicopter: The Key to Sustained Strategic Success” by Richard Harrop is a business leadership book that emphasizes the importance of maintaining a strategic, high-level perspective to achieve long-term success. Harrop uses the metaphor of “staying in the helicopter” to illustrate the necessity for leaders to rise above daily operations and view their organization and its environment from a broader perspective.

Key themes of the book include:

  1. Strategic Vision: Encourages leaders to develop and maintain a clear, long-term vision for their organizations.
  2. Adaptability: Stresses the need for organizations to be flexible and adaptable in response to changing market conditions.
  3. Leadership Skills: Discusses the qualities and skills necessary for effective leadership, including decision-making, communication, and the ability to inspire and motivate others.
  4. Continuous Improvement: Advocates for a culture of continuous learning and improvement within organizations.
  5. Balanced Perspective: Emphasizes balancing short-term operational demands with long-term strategic goals.

Through practical advice, case studies, and personal anecdotes, Harrop provides insights and tools for leaders to enhance their strategic thinking and ensure sustained success in their organisations.

Risks of not staying in the helicopter

If senior leadership gets “out of the helicopter” and becomes overly focused on day-to-day operations, several risks to the business can arise:

  1. Loss of Strategic Vision: Without a high-level perspective, leaders may lose sight of the long-term goals and vision of the organization, leading to a lack of direction and strategic focus.
  2. Inability to Adapt: Being too immersed in daily operations can make it difficult to notice and respond to broader market trends and changes, reducing the organization’s ability to adapt to new challenges and opportunities.
  3. Missed Opportunities: Leaders might miss out on identifying new opportunities for growth, innovation, or strategic partnerships because they are too focused on immediate issues.
  4. Operational Myopia: Overemphasis on short-term operational issues can result in neglecting important strategic initiatives, such as research and development, marketing, and expansion plans.
  5. Resource Misallocation: Resources may be allocated inefficiently, focusing too much on immediate problems rather than investing in strategic projects that ensure long-term success.
  6. Employee Disengagement: Employees may feel directionless and unmotivated if they perceive that leadership lacks a clear vision or strategic direction, leading to decreased morale and productivity.
  7. Competitive Disadvantage: Competitors who maintain a strategic perspective can outmaneuver the organization, leading to a loss of market share and competitive edge.
  8. Risk Management Failures: A lack of high-level oversight can result in inadequate risk management, leaving the organization vulnerable to unforeseen threats and crises.
  9. Innovation Stagnation: Innovation may stagnate if leaders are too focused on maintaining the status quo rather than exploring new ideas and fostering a culture of creativity.
  10. Leadership Burnout: Senior leaders might experience burnout from being overly involved in day-to-day operations, which can impair their ability to lead effectively and make sound strategic decisions.

Maintaining a balance between operational oversight and strategic vision is crucial for sustainable success and long-term growth.

Conclusion

In summary, while attention to daily operations is vital for the smooth running of any organization, senior leaders must not lose sight of the bigger picture. Richard Harrop’s concept of “staying in the helicopter” serves as a critical reminder of the importance of strategic oversight. By maintaining a high-level perspective, leaders can ensure their organizations remain adaptable, innovative, and competitive. Failing to do so can lead to a host of risks, from missed opportunities to operational myopia and beyond. Balancing immediate operational demands with long-term strategic vision is essential for sustained success and growth in today’s dynamic business environment.

Leveraging Generative AI to Boost Office Productivity

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Generative AI tools like ChatGPT and CoPilot are revolutionising the way we approach office productivity. These tools are not only automating routine tasks but are also enhancing complex processes, boosting both efficiency and creativity in the workplace. In the modern fast-paced business environment, maximising productivity is crucial for success. Generative AI tools are at the forefront of this transformation, offering innovative ways to enhance efficiency across various office tasks. Here, we explore how these tools can revolutionise workplace productivity, focusing on email management, consultancy response documentation, data engineering, analytics coding, quality assurance in software development, and other areas.

Here’s how ChatGPT can be utilised in various aspects of office work:

  • Streamlining Email Communication – Email remains a fundamental communication tool in offices, but managing it can be time-consuming. ChatGPT can help streamline this process by generating draft responses, summarising long email threads, and even prioritising emails based on urgency and relevance. By automating routine correspondence, employees can focus more on critical tasks, enhancing overall productivity.
  • Writing Assistance – Whether drafting emails, creating content, or polishing documents, writing can be a significant drain on time. ChatGPT can act as a writing assistant, offering suggestions, correcting mistakes, and improving the overall quality of written communications. This support ensures that communications are not only efficient but also professionally presented.
  • Translating Texts – In a globalised work environment, the ability to communicate across languages is essential. ChatGPT can assist with translating documents and communications, ensuring clear and effective interaction with diverse teams and clients.
  • Enhancing Consultancy Response Documentation – For consultants, timely and accurate documentation is key. Generative AI can assist in drafting documents, proposals, and reports. By inputting the project’s parameters and objectives, tools like ChatGPT can produce comprehensive drafts that consultants can refine and finalise, significantly reducing the time spent on document creation.
  • Enhancing Research – Research can be made more efficient with ChatGPT’s ability to quickly find relevant information, summarise key articles, and provide deep insights. Whether for market research, academic purposes, or competitive analysis, ChatGPT can streamline the information gathering and analysis process.
  • Coding Assistance in Data Engineering and Analytics – For developers, coding can be enhanced with the help of AI tools. By describing a coding problem or requesting specific snippets, ChatGPT can provide relevant and accurate code suggestions. This assistance is invaluable for speeding up development cycles and reducing bugs in the code. CoPilot, powered by AI, transforms how data professionals write code. It suggests code snippets and entire functions based on the comments or the partial code already written. This is especially useful in data engineering and analytics, where writing efficient, error-free code can be complex and time-consuming. CoPilot helps in scripting data pipelines and performing data analysis, thereby reducing errors and improving the speed of development. More on this covered within the Microsoft Fabric and CoPilot section below.
  • Quality Assurance and Test-Driven Development (TDD) – In software development, ensuring quality and adhering to the principles of TDD can be enhanced using generative AI tools. These tools can suggest test cases, help write test scripts, and even provide feedback on the coverage of the tests written. By integrating AI into the development process, developers can ensure that their code not only functions correctly but also meets the required standards before deployment.
  • Automating Routine Office Tasks – Beyond specialised tasks, generative AI can automate various routine activities in the office. From generating financial reports to creating presentations and managing schedules, AI tools can take over repetitive tasks, freeing up employees to focus on more strategic activities. Repetitive tasks like scheduling, data entry, and routine inquiries can be automated with ChatGPT. This delegation of mundane tasks frees up valuable time for employees to engage in more significant, high-value work.
  • Planning Your Day – Effective time management is key to productivity. ChatGPT can help organise your day by taking into account your tasks, deadlines, and priorities, enabling a more structured and productive routine.
  • Summarising Reports and Meeting Notes – One of the most time-consuming tasks in any business setting is going through lengthy documents and meeting notes. ChatGPT can simplify this by quickly analysing large texts and extracting essential information. This capability allows employees to focus on decision-making and strategy rather than getting bogged down by details.
  • Training and Onboarding – Training new employees is another area where generative AI can play a pivotal role. AI-driven programs can provide personalised learning experiences, simulate different scenarios, and give feedback in real-time, making the onboarding process more efficient and effective.
  • Enhancing Creative Processes – Generative AI is not limited to routine or technical tasks. It can also contribute creatively, helping design marketing materials, write creative content, and even generate ideas for innovation within the company.
  • Brainstorming and Inspiration – Creativity is a crucial component of problem-solving and innovation. When you hit a creative block or need a fresh perspective, ChatGPT can serve as a brainstorming partner. By inputting a prompt related to your topic, ChatGPT can generate a range of creative suggestions and insights, sparking new ideas and solutions.
  • Participating in Team Discussions – In collaborative settings like Microsoft Teams, ChatGPT and CoPilot can contribute by providing relevant information during discussions. This capability improves communication and aids in more informed decision-making, making team collaborations more effective.
  • Entertainment – Finally, the workplace isn’t just about productivity, it’s also about culture and morale. ChatGPT can inject light-hearted fun into the day with jokes or fun facts, enhancing the work environment and strengthening team bonds.

Enhancing Productivity with CoPilot in Microsoft’s Fabric Data Platform

The Microsoft’s Fabric Data Platform, a comprehensive ecosystem for managing and analysing data, represents an advanced approach to enterprise data solutions. Integrating AI-driven tools like GitHub’s CoPilot into this environment, significantly enhance the efficiency and effectiveness of data operations. Here’s how CoPilot can be specifically utilised within Microsoft’s Fabric Data Platform to drive innovation and productivity.

  • Streamlined Code Development for Data Solutions – CoPilot, as an AI pair programmer, offers real-time code suggestions and snippets based on the context of the work being done. In the environment of Microsoft’s Fabric Data Platform, which handles large volumes of data and complex data models, CoPilot can assist data engineers and scientists by suggesting optimised data queries, schema designs, and data processing workflows. This reduces the cognitive load on developers and accelerates the development cycle, allowing more time for strategic tasks.
  • Enhanced Error Handling and Debugging – Error handling is critical in data platforms where the integrity of data is paramount. CoPilot can predict common errors in code based on its learning from a vast corpus of codebases and offer preemptive solutions. This capability not only speeds up the debugging process but also helps maintain the robustness of the data platform by reducing downtime and data processing errors.
  • Automated Documentation – Documentation is often a neglected aspect of data platform management due to the ongoing demand for delivering functional code. CoPilot can generate code comments and documentation as the developer writes code. This integration ensures that the Microsoft Fabric Data Platform is well-documented, facilitating easier maintenance and compliance with internal and external audit requirements.
  • Personalised Learning and Development – CoPilot can serve as an educational tool within Microsoft’s Fabric Data Platform by helping new developers understand the intricacies of the platform’s API and existing codebase. By suggesting code examples and guiding through best practices, CoPilot helps in upskilling team members, leading to a more competent and versatile workforce.
  • Proactive Optimisation Suggestions – In data platforms, optimisation is key to handling large datasets efficiently. CoPilot can analyse the patterns in data access and processing within the Fabric Data Platform and suggest optimisations in real-time. These suggestions might include better indexing strategies, more efficient data storage formats, or improved data retrieval methods, which can significantly enhance the performance of the platform.

Conclusion

As we integrate generative AI tools like ChatGPT and CoPilot into our daily workflows, their potential to transform office productivity is immense. By automating mundane tasks, assisting in complex processes, and enhancing creative outputs, these tools not only save time but also improve the quality of work, potentially leading to significant gains in efficiency and innovation. The integration of generative AI tools into office workflows not only automates and speeds up processes but also brings a new level of sophistication to how tasks are approached and executed. From enhancing creative processes to improving how teams function, the role of AI in the office is undeniably transformative, paving the way for a smarter, more efficient workplace.

The integration of GitHub’s CoPilot into Microsoft’s Fabric Data Platform offers a promising enhancement to the productivity and capabilities of data teams. By automating routine coding tasks, aiding in debugging and optimisation, and providing valuable educational support, CoPilot helps build a more efficient, robust, and scalable data management environment. This collaboration not only drives immediate operational efficiencies but also fosters long-term innovation in handling and analysing data at scale.

As businesses continue to adopt these technologies, the future of work looks increasingly promising, driven by intelligent automation and enhanced human-machine collaboration.

Modular Operating Model for Strategy Agility

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One of life’s real pleasures, is riding a motorcycle. The sense of freedom when it is just you, machine and the open road is something only sharing enthusiast would truly understand. Inspired, I recently completed a hobby project building the Lego Set 42063. The building blocks of this Technic model constructs the BMW R1200GS Adventure motorcycle, arguably the best allrounder, adapted to handle all road conditions. The same building blocks can also be used to build a futuristic flying scooter, or shall I call it a speedster in true Star Wars style… While building the model I was marvelled by the ingeniousness of the design and how the different components come together in a final product – fit for purpose today but easily adapted to be fit for future.

Lego-Technic-modular

This made me think about business agility – how can this modular approach be used within business. We know that SOA (Service Oriented Architecture) takes a modular approach in building adaptable software application and in the talk on “Structure Technology for Success – using SOA” I explained a modular approached to design a Service Orientated Organisation (SOO), to directly contribute to the business success.

Recently I’ve also written about how to construct a business Operating Models that delivers. Such an operating model aligns the business operations with the needs of it’s customers, while it provides the agility to continuously adapt to changes in this fast changing technological ecosystem we live in. An Operating Model that delivers, fit for purpose today but easy adaptable to be fit for the future, in other words – a Modular Operating Model.

As the environment for a company changes rapidly, static operating models lack the agility to respond. Successful companies are customer centric and embrace continuous innovation to enhance the ability of the organisation to re-design it’s operations. This requires an Operating Model that incorporates the agility to be responsive to changes in business strategy and customer needs. A modular operating model enables agility in business operations with a design that can respond to change by defining standard building blocks and how to dynamically combine them. Modular blocks (with the specific operational complexity contained) simplifies managing complexity. This reduces the time to produce a new operational outcome, irrespective of this being a new services, product or just an efficiency improvement within an existing value chain.  

An example of applying modular thinking to a operational delivery methodology is covered in the blog post: “How to Innovate to stay Relevant”. In combining the core principles and benefits of three different delivery methodologies, Design Thinking, Lean Startup and Agile Scrum as modular building blocks, a delivery methodology are constructed that ensures rapid delivery of innovation into customer centric revenue channels while optimising the chances of success through continuous alignment with customer and market demand.

A modular operating model imbeds operational agility through the ability to use, re-use, plug and play different capabilities, processes and resources (building blocks) tech-TOMto easily produce new business outcomes without having to deal with the complexities which are already defined within the individual building blocks – just like a Lego set using the same set of standardised and pre-defined blocks to build completely different things. The focus is on re-using the blocks and not on the design of the blocks itself. Off course a lot of thinking has gone into the design of the different building blocks, but through re-using the same block designs, the model design time is focussed on a new/different outcome and not on a component of an outcome.

Designing modular capabilities, processes and resources that are used to design operating models have benefits not just in efficiencies and savings through economies of scale, but also in the reduction of time to market. These benefits are easier to accomplish in larger multi-divisional organisation with multiple operating models or organisations with complex operating models bringing together multiple organisations and different locations, where the re-use of modular operating model blocks bring demonstrable efficiencies – but is also possible for smaller organisations and start-ups.

If you want a Operating Model that Delivers and are agile to adapt to the challenges introduced by new technologies and digital business models – ensure the Target Operating Model (TOM) design methodology focusses on modular thinking from the offset and through the design process.

renierbotha Ltd has a demonstrable track record of compiling and delivering visionary Target Operating Models.

Talk to us – we can help you with the Digital Transformation to align your business operations and business model to the modern customers expectations.

 

Also read…

An Operating Model that Delivers

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Every organisation that I have worked with around the world, whether it is in London, Johannesburg, Sydney, Singapore, Dallas, Kuala Lumpir, Las-Vegas, Nairobi or New York, there was always reference to a Target Operating Model (TOM) when business leaders spoke about business strategy and performance. Yes, the TOM – the ever eluding state of euphoria when all business operations work together in harmony to deliver the business vision…sometime in the near foreseen future.

Most business transformation programmes are focussed to deliver a target operating model – transforming the business by introducing a new way of working that better aligns the business offering with it’s customer’s changing expectation. Millions in business change budgets have been invested in TOM design projects and 1000s of people have worked in these TOM projects of which some have delivered against the promise.

With the TOM as the defined deliverable, the targeted operational state and the outcome of the business transformation programme, it is very important that the designed TOM are actually fit for purpose. The TOM also has to lend itself to be easily adjustable in order to contribute to the agility of an organisation. The way the business is operating must be able to adapt to an ever changing technology driven world and the associated workforce. The quick evolving digital world is probably the main catalyst for transformation in organisations today – read “The Digital Transformation Necessity” for further insights…

Operating Model (OM)

The Operating Model uses key inputs from the Business Model and Strategy.

The Business Model focuses on the business’ customers, the associated product and service offerings – how the organisation creates value for it’s cliental – and the commercial proposition. Within the business model the business’s revenue streams and how those are contributing to the business value chain to generate profits, are decried. In other words, the Business Model envisages the What within the organisation.

Within the Business Strategy the plan to achieve specific goals are defined, as well as the metrics required to measure how successfully these are achieved. The business goals are achieved through the daily actions as defined within the Operating Model.

Typically an Operating Model takes the What from the Business Model in conjunction with the business strategy, and defines the Why, What, How, Who and With. It is the way in which the business model and strategy is executed by conducting the day to day business operations. Execution is key as no business can be successful by just having a business strategy, the execution of the operating model delivering the business strategy is the operative ingredient of success.

In order to document and describe how an organisation functions, the Operating model usually includes business capabilities and associated processes, the products and/or services being delivered, the roles and responsibilities of people within the business and how these are organised and governed within the business, the metrics defined to manage, monitor and control the performance of the organisation and then the underpinning Technology, Information Systems and Tools the business uses in delivering it’s services and/or products.

Analogy: A good analogy to describe the Operating Model is to compare it to the engine of F1 car. In 2016 the Mercedes Silver Arrow (the fastest car, driven by Lewis Hamilton (arguably the fastest driver), did not win because of engine and reliability problems. Instead the World Championship was won by Nico Rosberg, who had a better performing engine over the whole season. Nico benefited from a better operating model – he had the processes, data, systems and the people (including himself) to win. The mechanical failures that Lewis suffered, mostly not through fault of his own, were a result of failures somewhere within his operating model.

Target Operating Model (TOM)

The Target Operating Model (TOM) is a future state version of the Operating Model. To derive the TOM, the existing Operating Model is compared with the desired future state keeping the key aspects of an operating model in mind: Why, What, How, Where, Who and With. The TOM also cover two additional key aspects: the When & Where defined within the transformation programme to evolve from current to future states.

The difference between the “as is” Operating Model and the “to be” Target Operating Model, indicates the gap that the business must bridge in the execution of its Transformation Model/Strategy – the When and Where. To achieve the Target Operating Model usually require large transformation effort, executed as change & transformation programmes and projects.

ToBe (TOM) – AsIs (OM) = Transformation Model (TM)

Why >> Business Vision & Mission

What >> Business Model (Revenue channels through Products and Services – the Value Chain)

How >> Business Values & Processes & Metrics

Who >> Roles & Responsibilities (RACI)

With >> Tools, Technology and Information

Where & When >> Transformation Model/Strategy

Defining the TOM

A methodology to compile the Target Operating Model (TOM) is summarised by the three steps shown in the diagram below:

TOM Methodology
Inputs to the methodology:

  • Business Model
  • Business Strategy
  • Current Operating Model
  • Formaly documented information, processes, resource models, strategies, statistics, metrics…
  • Information gathered through interviews, meetings, workshops…

Methodology produces TOM Outputs:

  • Business capabilities and associated processes
  • Clearly defined and monetised catalogue of the products and/or services being delivered
  • Organisation structure indicating roles and responsibilities of people within the business and how these are organised and governed
  • Metrics specifically defined to manage, monitor and control the performance of the organisation
  • Underpinning Technology, Information Systems and Tools the business uses in delivering it’s services and/or products

The outputs from this methodology covers each key aspect needed for a TOM that will deliver on the desired business outcomes. Understanding these desired outcomes and the associated goals and milestones to achieve them, is hence a fundamental prerequisite in compiling a TOM.

To Conclude

An achievable Target Operating Model, that delivers, is dependant on the execution of an overall business transformation strategy that aligns the business’ vision, mission and strategy with a future desired state in which the business should function.

Part of the TOM is this Business Transformation Model that outlines the transformation programme plan, which functionally syncs the current with the future operating states. It also outlines the execution phases required to deliver the desired outcomes, in the right place at the right time, while having the agility to continuously adapt to changes.

Only if an organisation has a strategically aligned and agile Target Operating Model in place that can achieve this, is the business in a position to successfully navigate its journey to the benefits and value growth it desires.

renierbotha Ltd has a demonstrable track record of compiling and delivering visionary Target Operating Models.

If you know that your business has to transform to stay relevant – Get in touch!

 

Originally written by Renier Botha in 2016 when, as Managing Director, he was pivotal in delivering the TOM for Systems Powering Healthcare Ltd.

Top 10 Technology Trends Impacting Infrastructure & Operations for 2018

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Does your IT strategy include infrastructure, operations (I&O) practices and data center architectures that are sufficient to meet the demands of the digital business. Digital transformation requires IT agility and velocity that outstrips classical architectures and practices.

David Cappuccio, from Gartner outlines the top 10 trends that will impact IT operations (I&O) in 2018. Each will have an impact on how IT operates, plans, enhances internal skill sets, and supports the business.

 

Guest Blog: Original Article @ Gartner

Outside forces will shape IT’s journey towards a digital infrastructure.

Legacy infrastructure and operations (I&O) practices and traditional data center architectures are not sufficient to meet the demands of the digital business. Digital transformation requires IT agility and velocity that outstrips classical architectures and practices.

In 2018, IT will be increasingly tasked with supporting complex, distributed applications using new technologies that are spread across systems in multiple locations, including on-premises data centers, the public cloud and hosting providers.

David Cappuccio, vice president and distinguished analyst at Gartner, says I&O leaders should focus on 10 key technologies and trends to support digital transformation.

“These are not necessarily the top 10 technologies, or the hottest trends in IT, but rather the 10 trends we feel will have an impact on I&O teams over the next few years,” says Cappuccio. “Some are happening already, some are just beginning, but each will have an impact on how IT operates, plans, enhances internal skill sets, and supports the business.”

Strategic

Trend 1: Geo Planning
Outside factors including the European Union’s General Data Protection Regulation (GDPR), geo specific workloads and global and regional network access are driving IT to spend more time on geo planning as part of their longer term strategies. The long term objective is not to own a global infrastructure, but to build the infrastructure needed to support the business via partners, as well as leveraging an organization’s partner’s infrastructure to help support initiatives such as multiple network connections and infrastructure design and support.

Trend 2: The Intelligent Edge
Many digital business projects create data that can be processed more efficiently when the computing power is close to the thing or person generating it. Edge computing solutions address this need for localized computing power. For example, in the context of the Internet of Things (IoT), the sources of data generation are usually things with sensors or embedded devices. The intelligent edge serves as the decentralized extension of the campus networks, cellular networks, data center networks or the cloud. Organizations that have embarked on a digital business journey have realized that a more decentralized approach is required to address digital business infrastructure requirements.

Trend 3: Intent-based Networking (IBNS)
Gartner predicts that by 2020, more than 1,000 large enterprises will use intent-based networking systems in production, up from less than 50 today. Intent-based networking (IBNS) is not a product, or a market. Instead, it is a piece of networking software that helps to plan, design and implement/operate networks that can improve network availability and agility, which becomes increasingly important as organizations transition towards digital business.

With IBNS, rather than explicitly defining to the network what needs to be done, the software translates the business intent to determine the “correctness” of the network configuration before deployment. The system then continuously compares the actual and desired state of the running network.

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Tactical

Trend 4: APIs – Integration Economy
A digital business is supported by technology platforms in five areas: information systems; customer experience; data and analytics; IoT; and ecosystems. The ecosystems technology platform supports the creation of, and connection to, external ecosystems, marketplaces and communities. Application performance interface (API) management enables the digital platform to function.

Organizations should design APIs from the “outside in,” based on ecosystem requirements, not “inside out,” based on existing applications or technology infrastructure. “Ensure that your organization takes an ‘API first’ approach, designing APIs based on the requirements of your organization’s ecosystem,” says Cappuccio. “APIs designed in this way can be mapped to internal technology infrastructure. This approach is more effective than simply generating APIs based on existing infrastructure and data models.”

Trend 5: Reputation and Digital Experience
There are two interlinked trends impacting business today that have nothing to do with IT infrastructure, but everything to do with infrastructure design. Digital experience management (DEM) is the impact of presenting the right digital experience to customers. The experience could be mobile or web-based, and should be always available, continually improving and perform quickly and consistently. If any of these tenants are lacking, customer satisfaction is in peril. If customer satisfaction is in peril, especially in today’s social media savvy world, corporate reputation could quickly be damaged.

Trend 6: Beyond Traditional IT – New Realities
Business units are demanding agility, in opening new markets, taking on emerging competitors, bringing in new suppliers, and creating innovative ways of interacting with customers. Over 30% of current IT spend is not part of the IT budget, but overall responsibility for supporting these new initiatives, once they are tested and stabilized, will reside with traditional IT. Managing those new providers, managing workflows and managing new types of assets in this hybrid environment, regardless of where they are located, will become crucial to IT’s success.

Operational

Trend 7: DCaaS as a Strategy
In a perfect world, at least from the perspective of many business leaders, IT and the data center would be essentially a very agile provider of service outcomes, rather than the owner of the infrastructure. To do this organizations are creating a data center as a service (DCaaS) model, where the role of IT and the data center is to deliver the right service, at the right pace, from the right provider, at the right price.

“Making key short-term decisions can lead to a long-term strategy that incorporates the best of ‘as a service’ and the cloud without compromising IT’s overall goals to both protect and enable the business,” says Cappuccio. “In this manner, IT can enable the use of cloud services across the business, but with a focus on picking the right service, at the right time, from the right provider, and in such a way that underlying IT service and support does not get compromised.”

Trend 8: Cautious Cloud Adoption
For many enterprises the journey to the cloud is a slow, controlled process. Colocation and hosting providers have established private or shared clouds on their premises to provide customers some basic cloud services, enabling controlled migrations, staff skills training and a “safe” cloud environment as a stepping stone to increased cloud adoption in the future. As customers get comfortable with these services and costs, increased migrations to external providers are enabled via interconnect services. Using this partner ecosystem to enable an agile infrastructure is a rapidly emerging trend.

Trend 9: Capacity Optimization – Everywhere
Organizations need to focus on optimizing capacity and guard against stranded capacity – things that are paid for, but not really being used. This issue can be found both in existing on premise data centers and in the cloud. A change in culture is needed to fix this problem. Organizations must learn to focus not just on uptime and availability, but also on capacity, utilization and density. Doing so can extend the life of an existing data center and reduce operating expenditures from cloud providers.

Trend 10: Extended Infrastructure Management
The data center as the sole source of IT infrastructure has given way to a hybrid of on-premises, colocation, hosting, and public and private cloud solutions. These elements are being combined with a focus on providing business-enabling services and outcomes, rather than a focus on physical infrastructure. Enterprises must apply a future-looking, enterprise-wide “steady hand” to IT strategy and planning, and apply appropriate guardrails, or face the possibility of losing relevance, governance and enterprise agility.

 

Book Summary: “Staying in the Helicopter: The Key to Sustained Strategic Success” by Richard Harrop

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“Staying in the Helicopter: The Key to Sustained Strategic Success” by Richard Harrop is a business leadership book that emphasises the importance of maintaining a strategic, high-level perspective to achieve long-term success. Harrop uses the metaphor of “staying in the helicopter” to illustrate the necessity for leaders to rise above daily operations and view their organisation and its environment from a broader perspective.

Key themes of the book include:

  • Strategic Vision: Encourages leaders to develop and maintain a clear, long-term vision for their organisations.
  • Adaptability: Stresses the need for organisations to be flexible and adaptable in response to changing market conditions.
  • Leadership Skills: Discusses the qualities and skills necessary for effective leadership, including decision-making, communication, and the ability to inspire and motivate others.
  • Continuous Improvement: Advocates for a culture of continuous learning and improvement within organisations.
  • Balanced Perspective: Emphasises balancing short-term operational demands with long-term strategic goals.

Through practical advice, case studies, and personal anecdotes, Harrop provides insights and tools for leaders to enhance their strategic thinking and ensure sustained success in their organisations.

As a senior business leader, I highly recommend reading “Staying in the Helicopter: The Key to Sustained Strategic Success” by Richard Harrop. This book has been invaluable in helping me understand the importance of maintaining a high-level perspective while managing the complexities of daily operations. Harrop’s practical advice and compelling case studies provide the tools needed to balance immediate demands with long-term vision, ensuring sustained success and growth. This guide has enhanced my strategic thinking and enabled me to lead my organisation with greater clarity and foresight.