Lessons from Blockbuster: AI, Data & Change Management

March 18, 2024

Remember Blockbuster? Once a towering giant in entertainment, now a ghostly relic of the past— it stands as a cautionary tale of business evolution. Ignoring the shifting winds of customer preferences and the tidal wave of disruptive technology, Blockbuster found itself marooned on the shores of obsoleteness. Today's change leaders and organizations find themselves at a similar crossroads: embrace new ways of working and sail towards prosperous horizons, mirroring the success of Netflix, or risk stagnation by clinging to outdated ways of work, like Blockbuster? Businesses are sprinting towards AI adoption, data-informed decision making is on the rise, and change fatigue looms in a work landscape of constant, complex change. Let's dive into what this means for change leaders: 

AI Adoption and the Evolving Workforce: Surfing the Technological Swell

Blockbuster's downfall serves as a poignant reminder that organizations must not shy away from the power of artificial intelligence (AI), despite its potential disruptions. A recent Gartner study asked more than 500 HR leaders to identify their priorities and challenges for 2024. The verdict? 76% of HR leaders feel they will lag in organizational success if they don't implement AI in the next two years. The workforce is undergoing a metamorphosis as employees face pressure to learn new technology, embed it in their work, and demonstrate AI competency. According to a recent McKinsey Global Institute study, leaders should expect technology adoption to impact these major people-related areas: 

  • Retraining: teaching employees new or significantly different skills. 
  • Redeployment: shifting people resources to tasks or responsibilities of higher importance. 
  • Hiring: attracting new talent and people with future-ready skillsets. 
  • Contracting: filling skills gaps with contractors, freelancers, and temporary workers
  • Releasing: releasing employees, especially in industries where automation can significantly replace human labor. 

Organizations are struggling to embrace innovations while balancing the continuous demand for human-centric workplace design. Change management leaders, acting as guides through these turbulent waters, will need to equip employees with complex new skills, lead initiatives focused on building future-ready workforces, and instill continuous learning cultures across their organizations.

The Rise of Data-Informed Decision Making: Catching the Analytics Wave

Additionally, businesses are increasingly relying on data-informed decision-making processes, and change managers need to keep up to gain a competitive edge. In this era of "big data," relying solely on a smattering of Excel workbooks and PowerPoint presentations simply won't cut it. However, the change industry seems to lag on the data uptake. Why? Let's breakdown some resistance issues: 

  1. Data-competency: Data-informed change management requires change leaders to, well, change how they work and the tools they use to get the job done. This is a new skill set and it requires capability building for practitioners that aren't used to working with data. Investing in tools that can quantify change saturation won't help you if the data behind reports is unfamiliar to you. Competence development is critical for our industry to understand what our data sources should be, how we analyze them, and what is means for our change efforts. Mastering data literacy and defining clear parameters and guidelines are essential for future-ready change management.
  1. Traditional methodologies: Traditional change methodologies struggle to keep pace with the data revolution. Meanwhile, change leaders face mounting pressure to quantify change fatigue, risks, and impact at the enterprise level. In Why Change Management Skills Are Essential To Data-Driven Success, a Forbes study pinpoints "procedural resistance" as a key obstacle hindering the adoption of data analysis. While some individuals may not inherently oppose data, they're apprehensive about its integration into vital processes and scenarios. Future-ready practitioners must embrace flexible, customized, data-informed change approaches. At ChangeSync – our enterprise-change solution is designed to fill this gap in data leadership, governance, and best practice guidelines. Plus, our change management certification course teaches participants where and how to leverage critical change data.

  1. Data culture: Data-informed change management aims to empower strategic decision-making among change teams and business leaders. Yet, merely possessing the data isn't enough; its effectiveness hinges on executive leaders' ability to wield it wisely. Sometimes, leaders may opt to disregard data that challenges their current priorities, goals, or values. As highlighted by BARC, a prominent analyst firm for business software, data-savvy professionals often face hurdles due to management's inconsistent commitment to fostering a data culture, making informed decisions, and enhancing data management practices. To cultivate a truly data-informed culture, executive support and a well-defined change-data strategy are indispensable.

In today's evolving landscape, organizations face a stark choice: adapt to new ways of work or risk becoming the next Blockbuster, left behind by disruptive technologies like AI. Change leaders must also rethink traditional ways of working to match the pace of transformation and data sophistication. ChangeSync's proprietary approach, Organizational Change Design™ (OCD), acts as a guiding light for change leaders navigating these new, data-informed waters. By providing a holistic strategy encompassing resources, technology, culture, and processes, OCD ensures organizations and change teams stay ahead of the curve. As AI adoption and data-driven decision-making reshape industries, OCD becomes essential for staying future-ready, steering the change industry away from obsoleteness toward transformative success.


  1. McKinsey & Company, "Skill shift: Automation and the future of the workforce." (2018) 
  2. BARC Data Culture Survey 22, "How To Shape The Culture Of A Data-Driven Organization." (2022)
  3. Forbes, "Navigating Change Management In The Era Of Generative AI." (2023)
  4. Forbes, "Why Change Management Skills Are Essential To Data-Driven Success." (2022)
  5. Gartner, "Top 5 Priorities for HR Leaders in 2024." (2023)