BoardSnap is an iOS app that reads a weighted decision matrix whiteboard — options, criteria, weights, and scores — and produces a ranked summary with the winning option and the scoring logic.
Every team has decisions where gut feel isn't enough and someone needs to show their work. Vendor selection, technology stack choice, feature prioritization between competing options, go vs. no-go on a strategic bet — these decisions benefit from a structured matrix where criteria are weighted and options are scored against each criterion.
The whiteboard version of a decision matrix is fast to build and easy to debate. Write the options as rows, the criteria as columns, assign weights to each criterion (1-5 or percentage), score each option on each criterion (1-10), multiply, sum. The highest weighted total wins — or at least, the scoring makes it clear why the gut-feel winner isn't the mathematical winner, which is often the more useful output.
The problem is that a decision matrix on a whiteboard looks like a table of numbers. When the meeting ends, nobody can reconstruct the scoring rationale from a photo. Which option was preferred on which criterion? What was the weight assigned to 'implementation risk' versus 'feature completeness'? Those details are the decision's defensible rationale. They disappear with the whiteboard.
One sentence at the top: 'Which database should we use for the new analytics service?' or 'Which agency should we hire for the website redesign?' The decision question scopes the matrix.
Write each option as a row on the left side of the table. Label each row with the option name. Three to six options is the practical range — more than six makes the scoring tedious and the results hard to differentiate.
Write the evaluation criteria as column headers. Four to seven criteria is the usable range. Criteria should be independent of each other — avoid criteria that are really measuring the same thing twice. Examples: Cost, Implementation speed, Scalability, Team expertise, Vendor support, Migration risk.
In a row below the column headers (or above them), write the weight for each criterion: 1-5, 1-10, or percentage. Higher weight = more important. The team should agree on weights before scoring options — this surfaces real disagreements about what matters most.
For each cell, write a score (1-10, where 10 = best). Score one criterion at a time across all options before moving to the next — this keeps comparisons consistent. Write the raw score in the cell.
Multiply each raw score by the criterion weight. Write the result in the cell (or in a smaller number below the raw score). Sum the weighted scores for each option — write the total in a rightmost 'Total' column.
Open BoardSnap. The decision matrix is a grid with labeled rows (options), labeled columns (criteria), weight numbers, raw scores, and totals. BoardSnap AI reads the table structure, extracts scores, and identifies the highest-total option.
A structured decision matrix summary: the decision question, options and criteria listed, weights per criterion, scores per option per criterion, weighted totals, and the winning option identified. The output includes a short rationale — where each option scored highest and lowest — so the decision is defensible, not just a number.
The team was choosing between three database options. Six criteria, weights assigned by the CTO. BoardSnap read the full matrix — 18 scores across three options — and produced a ranked summary. The second-highest scoring option was chosen over the mathematical winner because of a non-scored criteria (team familiarity) that the team decided to add to the next iteration. BoardSnap's output made the trade-off explicit.
Five agencies, seven criteria, weighted by the marketing director. The matrix had 35 cells. BoardSnap read all of them and produced the ranked list. The client shared the output with the CEO as the decision memo — it showed not just the winner but exactly why the other four agencies ranked where they did.
BoardSnap AI reads the numbers from the board. If you write raw scores and weights, it can compute and describe the weighted totals. For best results, write the calculated cell totals on the board yourself before snapping — BoardSnap reads the numbers you write; it doesn't perform arithmetic independently.
Mixing scales introduces scoring errors. Standardize to one scale before scoring. If some criteria were scored on 1-5 and others on 1-10, write the normalized values on the board before snapping. BoardSnap reads what's on the board — normalization is your job.
BoardSnap flags ties in the output. A tie usually means the distinguishing criteria have equal weight — try adjusting weights or adding a tiebreaker criterion before making the final decision.
Snap the board, ship the action items in ten seconds.