Fixed Mindset Prioritisation Anti Patterns
Prioritisation done badly is slow, static, and easily gamed
Organisations often fall into the anti-pattern of using fixed mindset prioritisation frameworks that look flexible but, in reality, slow everything down and resist change. These frameworks look impressive, feel structured, and promise objectivity, but underneath, they’re rigid, gamed, and disconnected from fast-changing organisation needs.
You’ve probably seen these frameworks in action, they’re usually presented in big workshops, complex scorecards, or governance meetings that result in static plans nobody questions.
Some common fixed mindset frameworks include:
Weighted Scoring Models, where complex formulas replace honest conversations.
MoSCoW (Must, Should, Could, Won’t), where everything becomes a ‘must.’
RICE (Reach, Impact, Confidence, Effort), where stakeholders overstate reach and impact to push their agenda.
Eisenhower Matrix (Urgent/Important), which often pushes teams into reactive mode, focused on urgency rather than long-term value.
These plans become gospel. Teams spend months delivering what was once asked for, only to find the need has shifted. Meanwhile, stakeholders grow frustrated. Data Teams burn out, constantly reacting, firefighting, and losing focus.
In the end, these anti-patterns deliver work that’s “on time, on budget… and irrelevant.”
Prioritisation done badly is slow, static, and easily gamed
The Annual Wishlist
Stakeholders are asked to submit their “top 10 data needs” once a year, and those get locked into a static roadmap. Everything that changes mid-year is labelled “additional scope” rather than feeding into an evolving, continuously reprioritised backlog.
The Weighted Scoring Model Theatre
Spreadsheets full of formulas and weightings attempt to quantify value, complexity, risk, and urgency. It feels objective, but people quickly learn to game the system, inflating scores to push their own priorities.
The Parking Lot Mirage
New requests are parked for “future consideration”, but that parking lot becomes a backlog graveyard. Stakeholders lose interest when their new needs never surface on the priority list, and trust in the process erodes.
The Quarterly Steering Committee Stall
Prioritisation decisions are only made in infrequent committee meetings. By the time the committee meets, priorities have shifted, but can’t be changed until the next meeting cycle.
The First-In, First-Out Trap
Data requests are worked on in the order they’re received, with no efficient way to reassess and reprioritise importance. This leads to low-value, old requests clogging up the data team’s work queue, while new, high-value needs are forced to wait.
The Last-In, First-Out Flip
New requests jump straight to the top of the queue, pushing aside previously prioritised work. This constant disruption forces the data team to continually context switch, leaving high-value, planned work unfinished.
The VIP Shortcut
Senior leaders or high-profile initiatives bypass the prioritisation process altogether, jumping the queue and disrupting the team’s focus and delivery cadence.
The Shiny Object Chase
Exciting new technologies, tools, or trends suddenly become top priorities, framed as bold new strategic initiatives without going through the slow and rigid prioritisation process.
These days most of my prioritization is intuitive. I learn just enough about the problem, the user and the outcomes to define a solution and when that happens, the prioritization is obvious (except when I have dependencies). What is the better alternative to the list above? I use a simple 4x4 for risk and value evaluation.
Urgh... These all sound far too familiar 😞