Better Deciding



Main Challenge: no decision-making process

Without a roadmap or consistently practicing with decision tools, techniques and team processes - it is tough for executives and staff to improve over time.

Secondary challenges:


siloed Expertise

Every business uses a system that comes with its own peculiar taxonomy, protocols, and tools. This leads to confusion between their esoteric knowledge keepers - and the organization suffers as a result with poor decision making and skill transfer across departments. 

These siloed 'decision cohorts' present an intimidating barrier to potential outside entrants, who may possess fresh insights. Small decision cohorts are vulnerable to prematurely converging on a poor choice because they typically share similar backgrounds.

Domain specific decision-making skills can be lost as people move up or laterally within organizations. This results in skills abandonment, instead of progressively building upon a common, easy to apply decision system ALL employees use on a regular basis.


Most systems can't adapt to handle complexity with multiple stakeholders, competing priorities, timelines, risk profiles, and scenarios. 

poor recall

Most systems have a mnemonic or other gimmick to help with recall, but most of the time people don't even remember the mnemonic, let along the words each letter represents. If they do by chance remember the word it still may not be clear what they are supposed to do with that word.

A good system will tap into people's naturally powerful recall abilities by using imagery, logical themes, sound, and story.


Most decisions are 'medium complexity' that front-line and executives need help with on a fairly regular basis, however the system they know may be either too simplistic (pro/con list, weighted factors spreadsheet, forced paired comparison) or overly complex (scenario planning with decision trees) to strike the right balance between effectiveness and intuitive ease of use.

infrequency of use

If the current system cannot help solve everyday personal and business decisions, then it will be used infrequently, requiring refresher training and few opportunities to adapt the decision system to their own unique style and preferences.

No automation

Some decisions are transactional or would benefit from tapping into data. Both types present opportunities for automation, allowing people to focus on decision exceptions and adjusting the decision model. Analytics and artificial intelligence allow for faster, better decisions.


People don't have time to learn decision making, which requires learning from multiple disciplines, such as:

  • Business Strategy
  • Product Management
  • Psychology
  • Group Dynamics
  • Sociology
  • Project Management
  • Management Accounting