The Future of Strategic Change: Predictive Business Intelligence

The Future of Strategic Change: Unleashing the Power of Predictive Business Intelligence.

A revolution is coming – a revolution which will be peaceful if we are wise enough, compassionate if we care enough, and successful if we are fortunate enough – but a revolution is coming whether we will it or not.” JFK.

Introduction

Truly significant changes in business capability occur only once in a generation. While the way leaders manage strategic change has remained largely unchanged for the past 30 years, a combination of converging capabilities has now sparked the largest transformation in three decades.?

This article presents an overview of the systemic causes behind the current failure rates in change initiatives, unveils the technology-led solution poised to address these challenges, and outlines the core elements of transformation necessary to turn this vision into reality.?

A Look Forwards (The Future of Change)

It's 2026, and Jenny, a senior business leader responsible for a 2000-person strategic change function, has successfully implemented a Predictive Business Intelligence Capability in her Change Organization.

During her train journey to work, Jenny dives into the latest predictive analytics dashboards and insights. These provide realistic forecasts of expected benefits, costs, and ROI for each strategic change initiative. From this, she is able to identify a poorly trending project and makes a note to investigate further at the office.

Once at the office, Jenny gathers her team in the Strategy Execution Office to assess the current situation. Leveraging predictive scenario modeling, they reallocate resources and re-prioritize backlogs to maximize progress on strategic objectives. They identify and eliminate non-strategic deliverables that had crept into their workload and proactively implement mitigation actions for anticipated challenges on the horizon.?

Having an objective, independent, and accurate view of future reality empowers Jenny's team to address problems at their root cause. Though initially uncomfortable, they recognize the value of facing potential challenges head-on, allowing them to make proactive decisions and drive effective change.?

In the afternoon, Jenny attends the Change Investment Board meeting, engaging with key stakeholders to discuss the progress of her major strategic initiatives. They explore options to reduce costs and enhance benefits. Using predictive business intelligence, Jenny presents three scenarios that have been modeled to accommodate rapidly changing circumstances. Each scenario includes realistic forecasts for benefits, costs, and ROI. The stakeholders are impressed by the transparency and clarity of the choices presented, and they lend their support to the recommended approach.?

Before heading home, Jenny reflects on the productive day she has had utilizing predictive business intelligence to drive strategic change. She feels a profound sense of accomplishment, knowing that the adoption of this approach has revolutionized the way change is executed within the organization.

Strategy is turning into reality, benefit projections have doubled, cost projections have halved, and her team now has a more engaging and impactful role compared to the administrative-heavy world of the past.?

Finally, the business is able to effectively and efficiently turn strategy into reality every time.

This may seem futuristic but the vast majority of this capability, and the benefit it brings, are available today - with the remainder expected to be in place within the next 2-3 years through the maturing capabilities of AI and system learning.?

A Look Backwards (The History of Change)

The purpose of change is to achieve a specific outcome by investing a certain amount. However, the focus on realizing benefits and obtaining a solid return on investment (ROI) has often been neglected in the change industry. While people may talk about benefits at the start of a project, it is rare to find realistic projections or evidence of these benefits and ROI as the initiative progresses.?

Despite advancements in agile methodologies and SaaS software tools, the approach to change at the leadership level has changed very little in the past 30 years. Oversight and decision-making processes are still largely based on subjective information, personal opinions, and a reliance on hope and expectation. This is often managed by a cottage industry of Project Managers and Project Management Offices (PMOs).?

While change management has evolved to emphasize collaboration, agility, empowerment, diversity, and continuous learning, there is a significant lack of focus on the business aspects, such as business benefits and strategy execution.

Despite the high cost associated with change functions, it is clear that this approach simply does not work. The staggering $48 trillion is invested in change projects each year is still plagued by a 70% failure rate, which should be extremely concerning and unacceptable to any organization.

Ironically, the very function of change itself has become the slowest and most resistant system to change. The industry is in dire need of a transformation to prioritize business focus, realistic benefit projections, and effective strategy execution. Without addressing these fundamental issues, the cycle of high costs and failure rates in change projects will persist, hindering organizations from achieving their desired outcomes.?

Why is Traditional Change Failing?

In many large-scale strategic initiatives, leaders often find themselves navigating blindfolded, their hands tied, and their problem-solving skills rendered ineffective. The lack of clarity in perceiving future realities, anticipating problems, and understanding their root causes severely hinders their ability to make informed decisions and progress towards achieving strategy.?

A primary factor contributing to this predicament is the reliance on traditional people-driven systems. These systems, built upon historical data and projections rooted in personal opinions, fall short in providing an unbiased and objective view of the future reality. The data generated by people introduces significant inaccuracies and detachment from the actual progress being made, distorting leaders' perspectives and making it difficult to identify the real problems that need solving.

Moreover, the evolution of technology to support people-driven systems has resulted in a proliferation of disconnected specialist systems, which only exacerbate the underlying issues. These systems, often narrowly focused and lacking integration, struggle to capture the interconnected nature of complex change initiatives. In contrast to the interconnectedness of real-life scenarios, the systems used for management fail to reflect this reality. As a result, leaders face challenges in perceiving the true reality of their change efforts, impeding their ability to navigate them effectively toward success.?

To make matters worse, these systems are too often filled with poor quality data. Many organizations grapple with messy, incomplete, short-term data that is plagued by inaccuracies. This undermines the reliability of generated insights, potentially leading to misleading conclusions and eroding trust in the available information. Consequently, decision-makers lose confidence in the content and may resort to relying on intuition, which unfortunately is often even less accurate in this context.

Business leaders often struggle to acknowledge the ineffectiveness, costliness, and inefficiency of their current organizational state. The prevailing issue is the widening gap between expectations and reality - also known as strategic divergence. This gap will often span strategic progress, cost-benefit analysis, and return on investment. However, the inherent limitations of the existing system often prevent the identification of strategic divergence before it's too late.

The following symptoms can serve as indicators of strategic divergence:?

• Impeded visibility of strategic/business progress: A lack of clear visibility into the progress and performance of strategic initiatives, making it difficult to assess their effectiveness and adjust course if needed.?
• Disconnect between strategy and delivery: Misalignment between strategic objectives and their execution, resulting in strategies that fail to be effectively translated into actionable plans and tangible outcomes.?
• Slow velocity, wastage, and inefficiency: Sluggish progress, excessive resource waste, operational inefficiencies, and a lack of alignment between different departments or teams, leading to suboptimal outcomes and a lack of progress.
• Ineffective resource allocation: Inconsistent distribution of resources, including budget, personnel, and time, across different strategic initiatives. Some projects may receive excessive resources while others are neglected, hindering progress due to imbalanced allocation.?
• Lack of transparency and communication: Insufficient open and transparent communication regarding strategic initiatives, progress, and challenges, resulting in confusion, silos, and breakdowns in collaboration between teams and departments.
• Absence of early warnings, late-breaking crisis, and cost overruns: Frequent occurrence of unexpected issues, emerging crises, and budget overruns, indicating poor planning, risk management, or a lack of coordination within the organization.
• Limited agility and responsiveness: Struggles in effectively responding to changes in the external environment or market conditions, displaying slow or inadequate responses to emerging opportunities or threats, indicative of a lack of strategic agility.?
• Ineffective risk management: Facing recurring challenges and disruptions that were inadequately anticipated or mitigated, highlighting a lack of proactive risk management practices and an inability to navigate unforeseen obstacles.?
• High employee turnover or dissatisfaction: Experiencing a high rate of employee turnover, low employee morale, or widespread dissatisfaction.

What's the Answer? (Predictive Business Intelligence)?

Overall, predictive business intelligence offers a transformative approach that combines the power of technology with human expertise. It enables organizations to harness data-driven insights, make informed decisions, and achieve greater success in their projects, all while realizing significant cost savings compared to traditional project management approaches.?

• Independent/Objective View of the Truth: Predictive business intelligence provides an unbiased and objective view of the truth, enabling organizations to see the reality of their projects and initiatives. It eliminates subjective biases and allows for a clear understanding of the current situation. By uncovering hidden insights and trends, organizations can identify and address underlying issues and challenges, leading to better decision-making and improved outcomes.?
• Business/Strategic Focus: By utilizing predictive business intelligence, organizations can align their delivery efforts with their overall business goals. It enables a strategic approach to project management and ensures that projects and initiatives are focused on delivering value and contributing to the strategic objectives of the organization. This alignment minimizes wasteful efforts and ensures that resources are directed towards the most impactful initiatives.?
• Realistic Long-Term Forecasts: Predictive intelligence enables organizations to generate realistic long-term forecasts of costs, benefits, and return on investment (ROI) for their projects. By analysing historical data and using predictive modelling techniques, organizations can estimate potential outcomes with greater accuracy. This allows for more reliable financial planning, resource allocation, and decision-making.
• Scenario Modelling/Simulation: Organizations can conduct scenario analysis, exploring different paths and options for their projects. Predictive business intelligence enables them to simulate various scenarios and evaluate the potential impact of different decisions. By considering multiple possibilities and their outcomes, leaders can make informed choices that lead to the best possible results for the organization, mitigating risks and capitalizing on opportunities.?
• Automated Resource Allocation: Predictive business intelligence helps organizations optimize the allocation of scarce resources. By analysing data and identifying areas of inefficiency, organizations can allocate resources strategically, ensuring that they are used where they are most needed and can generate the highest value. This prevents unnecessary resource waste and promotes efficiency throughout the organization.?
• Addressing Root-causes of Waste/Inefficiency: Predictive business intelligence helps identify the root causes of waste and inefficiency in projects. By analysing historical data, identifying patterns, and detecting bottlenecks, organizations can understand the underlying issues that contribute to waste and inefficiency. This knowledge allows them to implement targeted solutions and improvements, reducing waste, enhancing overall efficiency, and delivering better outcomes.?

How Do We Adopt This New Reality??

The adoption of predictive business intelligence is crucial in addressing the inherent structural problems of the current status quo. This technology-led capability provides a comprehensive solution that goes beyond blindly trusting data. By combining system intelligence with human instinct, organizations gain valuable insights and empower themselves to make better choices.?

Contrary to common belief, predictive business intelligence has been available for many years, and with the emergence of AI capabilities, this field is rapidly maturing and evolving.

Here are the key principles of predictive business intelligence:?

• Data Quality and Cleansing: To build reliable predictive models, it is essential to have high-quality data. This involves assessing data quality, identifying and resolving any issues or inconsistencies, and cleansing the data to eliminate errors or outliers. Data quality and cleansing are critical to ensure the accuracy and reliability of predictive insights.?
• Data Integration: The next building block is the integration of data from various sources within the organization. This involves collecting and consolidating data from different systems and databases, ensuring that it is accurate, complete, and standardized. Data integration lays the foundation for accurate analysis and prediction.?
• Data Housing: Creating a centralized data repository is crucial for storing the data. A well-designed repository allows for efficient data retrieval, integration, and analysis. It provides a solid infrastructure for predictive analytics by organizing data in a structured and accessible manner.?
• Advanced Analytics: The application of advanced analytics techniques enable organizations to extract meaningful patterns, relationships, and insights from the integrated and cleansed data. Advanced analytics helps in developing predictive models and algorithms that can generate accurate forecasts and predictions.?
• Data Visualization and Reporting: Effective visualization and reporting capabilities are vital for communicating predictive insights to decision-makers. Clear and concise reports help in presenting predictions, trends, and recommendations in a digestible format.?
• Collaboration and Human Expertise: Predictive business intelligence is not solely reliant on technology. Collaboration between data analysts, domain experts, and business leaders is essential. Human expertise and insights play a crucial role in interpreting predictive results, validating predictions, and making informed decisions based on the insights generated by the predictive models.

But Isn’t Change Too Complicated For This to Work??

At its core, change management can be simplified to a few key components. This includes clearly defined business goals, a manageable number of work items, and a summary-level understanding of teams and required skills.

By keeping the focus on these foundational aspects, the essence of change can be effectively managed.?The building blocks of change are inherently simple, but people and the abundance of tools can often complicate things unnecessarily.

Instead of focusing on the fundamental elements that drive change, individuals often feel compelled to demonstrate their expertise or worth by using an array of tools and adding layers of complexity that hinder progress.?The proliferation of these specialized tools, and the belief that more functionality equates to better results, can lead to a convoluted approach to change management that rarely works.?

To combat this, it's important to recognize that while detail and specificity have their place, they should be managed within lower-level systems. By adopting a summary-level approach and leveraging predictive business intelligence, organizations can gain valuable insights without getting bogged down in excessive complexity. This allows leaders to maintain a clear focus on the overarching direction of the initiative while empowering lower-level systems to handle the operational intricacies.??

Examples of how predictive intelligence is used in different industries to manage complex business environments include:?

• Gaming: The gaming industry employs predictive intelligence for player behaviour analysis, dynamic in-game advertising, game balancing, and fraud detection.?
• Financial Services: Banks, insurance companies, and investment firms leverage predictive intelligence for fraud detection, credit scoring, risk assessment, and stock market predictions.?
• Aviation: Predictive intelligence in aviation is used to anticipate maintenance issues, optimize operations, and enhance safety and efficiency in the industry.?
• Healthcare: Predictive intelligence plays a crucial role in healthcare for disease prediction, patient monitoring, early intervention, drug discovery, and optimizing healthcare resource allocation.?
• Transportation: Predictive intelligence helps transportation companies in route optimization, demand forecasting, predictive maintenance of vehicles, and real-time traffic prediction.?

Predictive intelligence is also used in a wide range of functions inside businesses, examples include:

• Sales and Marketing: to help improve customer targeting, lead generation, and sales forecasting.?
• Supply Chain Management: to optimize operations by forecasting demand, optimizing inventory, and anticipating disruptions.?
• Financial Analysis and Risk Management: to aid in financial forecasting, credit risk assessment, fraud detection, and investment decisions.?
• Human Resources: to optimize workforce planning, talent acquisition, and employee retention.?
• Customer Relationship Management (CRM): to enhance customer relationship management and improve customer experience.?

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How does Predictive Technology-led Change Differ from Traditional Approaches??

The difference between Predictive Technology-led change and traditional change management is the shift towards data-driven decision-making, proactive risk mitigation, and real-time adaptability that Predictive Technology-led change management brings compared to the more experience-based and reactive nature of traditional change management.

Here are the key distinctions:?????

• Business Outcomes vs. Technical Delivery: Predictive Technology-led change management prioritizes achieving specific business outcomes and realizing benefits, whereas traditional change management focuses more on the technical aspects of delivering a solution.?
• Data-Driven vs. Experience-Based: Predictive Technology-led change management relies on data analysis, predictive models, and system intelligence to make decisions, while traditional change management relies more on personal experience, intuition, and historical knowledge.?
• Proactive vs. Reactive: Predictive Technology-led change management takes a proactive approach by using predictive analytics to anticipate and prevent issues before they occur, whereas traditional change management tends to react to issues as they arise.?
• Realistic Forecasting vs. Historical Analysis: Predictive Technology-led change management focuses on forecasting future outcomes and trends based on data analysis, whereas traditional change management often relies on analysing past experiences to inform decisions.?
• Automated Resource Optimization vs. Manual Allocation: Predictive Technology-led change management optimizes resource allocation through data analysis and predictive models, while traditional change management often relies on manual allocation based on experience and estimation.?
• Real-Time Monitoring and Adaptability vs. Predefined Plans: Predictive Technology-led change management enables real-time monitoring, providing organizations with insights to make informed decisions, adapt strategies, and optimize execution. In contrast, traditional change management often follows predefined plans without the same level of real-time insights and adaptability.?

How Will This New Future Unfold?

To fully harness the substantial benefits of technology-led change, organizations must undergo a transformation process that encompasses various aspects, similar to the agile transformation that preceded it. This transformation will involve a mixture of mindset, culture, roles, tools, and processes, and will primarily occur at the leadership layer of the organization, in contrast to Agile, which often operates at the team level.?

One significant difference in this transformation is the need to adapt in the midst of a rapidly changing and evolving world. What took years or months to bring to market a decade ago is now likely to emerge in a matter of weeks or even days, thanks to the capabilities of AI and machine learning.

The AI industry is booming, with over 13,000 AI companies in the US alone, specializing in various areas that directly apply to the change management space. These specialized capabilities will continuously mature over time, presenting organizations with a constant stream of opportunities and advancements.?

To leverage this evolving landscape, organizations need to make the decision now that technology-led change is the future. They must embrace agility and iteration - concepts often discussed by the change industry, but seldom applied effectively to their own capabilities. The ability to adapt and iterate rapidly will be essential in navigating the fast-paced world of technology-led change.?

In this context, there will be a need to swap in and swap out technologies and capabilities as new advancements emerge. Rather than implementing a fixed plan for managing change, organizations must be able to flex; riding the new wave of technologies and approaches. This mindset allows them to seize opportunities as they arise and leverage the most relevant and effective tools for their specific strategic change needs.?

Predictive Business Intelligence has the potential to be applied to any area of a business, regardless of its size. Whether it's at the organizational level, a product, a strategic program, or a smaller project - the power of predictive insights brings significant benefits that drive success.

From marketing and sales to operations and finance, predictive analytics will uncover valuable insights, optimize processes, and enhance decision-making across the entire organization.?

Waiting for the perfect moment or trying to implement a massive transformation all at once will not be the most effective approach.

In the rapidly evolving landscape of Predictive Business Intelligence, its better to get started and learn as you go.?Taking small steps and implementing incremental changes allows organizations to gain practical experience, understand the specific needs of their business, and adapt their strategies accordingly. This ensures that the implementation of Predictive Business Intelligence remains relevant and effective, as it evolves in tandem with emerging technologies and industry trends.

Conclusion?

In conclusion, as forward-thinking business leaders, it is crucial for us to recognize the profound revolution underway and the tremendous opportunities it presents for our organizations. Predictive Business Intelligence represents the most significant change in over 30 years and the top level of leadership - finally granting business leaders with the capability to execute our strategies with accuracy and confidence. It is an opportunity to propel ourselves to new heights of success and one we simply cannot afford to ignore.?

By embracing Predictive Business Intelligence, we unlock a whole new level of strategic progress, improved benefits, and cost savings. The ability to leverage predictive insights to identify valuable work, optimize efficiency, and strategically allocate resources will be a true game-changer for our organizations.?

It is important to note that this transformation can be iterative. It may require a phased approach and continuous improvement, but the key is to get started and learn how to reap the benefits. Taking that initial step is paramount in unlocking the immense potential and reaping the early benefits of this ground-breaking shift.?

Not only will we experience tangible economic advantages and measurable impact on our strategic objectives, but we will also gain a substantial competitive advantage in the market. With the agility to rapidly adapt to changes and shorten our time-to-market, we will firmly establish ourselves as industry leaders, leaving competitors struggling to keep up.?

Predictive Business Intelligence offers us a unique opportunity to redefine how we approach change initiatives and drive remarkable growth in our industries.

Let's not just watch from the sidelines; instead, let's become champions of this revolution. By embracing Predictive Business Intelligence, we can lead the way, ride the wave of change, and propel our organizations to unparalleled success.

Now is the time to seize this transformative power and position ourselves as trailblazers in the business world.?

About the Author

Stephen Ram

Stephen, a founding partner at Cedus, brings 28 years of experience in leading strategic change for renowned organizations worldwide. He and his colleagues at Cedus work closely with business leaders to transform their internal change capability.

Cedus specialize in driving strategic change through the use of predictive business intelligence. Their approach is centered around trust, thought leadership, client value, and partnership. Over the last 10 years, they have been at the forefront of this movement, helping world-leading organizations achieve their strategic goals efficiently and effectively at all levels of their business. Find out more at: cedus.co.uk