Digital Strategy, Operating Models & Technology Implementation Insight

Expert guidance in business technology strategy, leadership, and implementation in response to digitally-driven disruption of traditional business models. From emerging new operating models to strategies that put data at the heart of your business; overcoming cultural hurdles to what makes a digital leader; achieving enterprise agility to creating a culture that supports continuous experimentation — you’ll be on the cutting edge of the factors that are critical to successful digital transformation.

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The team is the fundamental unit of organizational work, not the individual. But the ways we manage our teams — and thus our talent — often set us up for systemic gaps and increasing challenges (versus continuous improvement) over time. Today’s executives face two ongoing complex problems: business strategy and people leadership. The invisible nature of these talent issues makes solving them a strategic need through HR capacity building over time.
The COVID-19 pandemic has posed unprecedented challenges to businesses across all sectors and throughout the world. Risk management systems and contingency measures have been put to the test, and as is so often seen in moments of crisis, many have been found wanting. The result? A real need now exists to determine what is meant by business resilience and how to apply it to organizations’ different operating models.
Cutter Consortium Senior Consultant Barry M. O’Reilly introduces the concept of residuality theory and its application to the complex relationships that exist between different risks in the modern business environment. Expanding on the issues of complexity versus complication in the world of enterprise software, O’Reilly shows how the principle of residuality enables organizations to anticipate the impact of chains of interconnected risks.
Noah Barsky explores some key shifts in mindset that effective risk management will require, such as making risk management the responsibility of all, avoiding silos, looking at issues that are important but not urgent, and building a culture that can ask, “Why?” Barsky focuses on the need to not only connect the dots between different risk areas, but also between risk management and other corporate planning and monitoring activities.
Payson Hall explores the general con­text of risk management, noting the conflict between efficiency and resilience in organizations employing Lean practices to reduce their costs at the expense of robust risk management. Such approaches may beat the odds in the short term but lead to dangerous exposure when times are hard, as has been observed during the current global pandemic. Hall discusses ways in which a modest investment can provide vital hedging against catastrophe.
Cutter Consortium Fellow Bob Charette explores the current state of risk management in a world of repeated failures to adopt the lessons of the past, examining several of the most common ways in which risk management is failing and the reasons why. In his analysis, different areas of risk form a broader “risk ecology,” in which risks interact in complex ways, and isolated analysis and manage­ment of each area has the potential to increase risk in unforeseen ways.
In the second installment of their webinar series, “Using AI/Machine Learning to Manage Risk,” Cutter Senior Consultants Carl Bate, Michael Eiden, Craig Wylie, and Tom Teixeira answered some questions about new risk models that utilize artificial intelligence (AI) and machine learning (ML) to understand and respond to the changing business landscape.
Project schedule risk management using modeling and simulation tools and techniques is a tried and proven best practice in organizations and industries that strive to do more with less. However, there are some challenges associated with this methodology, and the intent of this Executive Update is to help those who strive for excellence in project management of complex projects to see how proactive risk management can be done successfully.