QSPM: The Quantitative Strategic Planning Matrix Explained

By Brian Tr · Updated Oct 10, 2026

The QSPM (Quantitative Strategic Planning Matrix) is a decision tool that ranks alternative strategies. It takes the weighted external and internal factors from your EFE and IFE matrices, scores how attractive each strategy is against each factor, multiplies by the weights, and adds the results. The strategy with the highest Sum Total Attractiveness Score wins.

This guide covers where the QSPM fits in Fred David's strategy-formulation framework, the six steps, a worked example with made-up numbers, a template, and the limits you should respect before betting money on the result.

Key Facts

• What it is: a grid that compares feasible strategies side by side on the same weighted list of external and internal factors.
• Where it sits: the single tool in the decision stage, the third stage of David's framework, after the input stage and the matching stage (Torlak and Sanal).
• Inputs: factors and weights come straight from the EFE and IFE matrices. Candidate strategies come from matching tools such as SWOT, SPACE, BCG, IE, and the Grand Strategy matrix.
• Key terms: AS is the Attractiveness Score, TAS is the Total Attractiveness Score (weight times AS), and the Sum Total Attractiveness Score adds the TAS values down each strategy column.
• Scoring scale: The key in David's framework runs from 1 (not attractive) to 4 (highly attractive). A smaller or larger range is allowed, set by how many strategies you compare (Torlak and Sanal; David, David and David, 2016).
• Origin: introduced by Fred R. David in a 1986 Long Range Planning article, "The Strategic Planning Matrix: A Quantitative Approach."
• Biggest limit: it always requires intuitive judgment, and it is only as good as the information beneath it.

What is the QSPM?

David's framework has three stages. The input stage summarizes basic information with the EFE matrix, the Competitive Profile Matrix (CPM), and the IFE matrix. The matching stage generates feasible strategies with SWOT, SPACE, BCG, IE, and Grand Strategy matrices. The decision stage has one tool: the QSPM. A published case study of David's framework describes it this way: the QSPM uses information from stage one to evaluate the feasible alternatives that stage two identified, and it gives an objective basis for choosing among them.

Here's the problem it solves. After a SWOT or TOWS session you usually have a long list of ideas. Nine strategies, say, and everyone has a favorite. A TOWS matrix is good at generating them but says nothing about which is best. David and his co-authors point out that a SWOT can't rank the factors by importance or rank the strategies it produces, and that it has no numbers. The QSPM fills both gaps.

It works because the logic is simple. A strategy is attractive to the extent that it helps you capture opportunities, reduce threats, use strengths, and fix weaknesses. Score each strategy against every factor that matters, weight the scores by how much the factor matters, and the total tells you which option does the most good.

The three-stage framework

The QSPM can't invent strategies. It depends completely on the first two stages. If the factor lists are weak or the strategy list leaves out the best option, the arithmetic will faithfully rank the wrong things.

QSPM vs the other matrices

People often confuse the QSPM with its neighbors because they all use weights and scores. The difference is the job each one does.

The closest cousin is the general-purpose decision matrix. Both multiply weights by scores. The difference is where the criteria come from. A decision matrix lets you pick any criteria. The QSPM draws its criteria from the full EFE and IFE analysis, so every key opportunity, threat, strength, and weakness gets a vote. That makes it more demanding to build and harder to cherry-pick.

How to build a QSPM, step by step

David's 2016 paper lays out six steps. Here they are in plain terms.

Step 1: List the key external and internal factors

Pull them from your EFE and IFE work. The paper suggests at least 10 and no more than 20 of each, so up to 40 rows in total. State them specifically, with a number where possible. "Healthy eating among people aged 16 to 36 is growing 12% a year" beats "more people eat healthy." Vague factors make vague decisions.

Step 2: Copy the weights

Weights show how important each factor is for succeeding in your industry. They must sum to 1.0 for the external factors and to 1.0 again for the internal factors. In the QSPM you carry over the weights you already set in the EFE and IFE matrices. Don't re-weight to suit a favorite strategy.

Step 3: List the alternative strategies

Put them across the top row. They usually come out of a SWOT analysis or TOWS matrix. Write them specifically: "add 30 sales reps in California" instead of "expand to California." Firms rarely have the money to do everything, so be honest about the strategies that are actually in contention. You can compare any number of strategies at once, or compare them in sets.

Step 4: Assign Attractiveness Scores (AS)

Work row by row. For each factor, ask: does this factor affect the choice between these strategies? If yes, score every strategy on that row. If no, put a dash in every column for that row.

The scale has a simple key: 1 means not attractive, 2 somewhat attractive, 3 reasonably attractive, and 4 highly attractive. "Attractive" means how well that strategy helps you use a strength, fix a weakness, capture an opportunity, or avoid a threat, compared with the other strategies in the set. Two rules from the 2016 paper:

• Work across the row, not down the column. You're comparing strategies against one factor at a time.
• Never give two strategies the same AS in one row. If a factor matters, it should separate the options. If you can't separate them, the factor probably doesn't affect the choice, and a dash is the right entry.

With five or more strategies on the table, a row can't stay within 1 to 4 without repeating a number, so widen the scale to match the number of strategies. The paper says the range can run from 1 to 2 up to 1 to 10, depending on how many strategies you compare.

Step 5: Compute the Total Attractiveness Scores (TAS)

Multiply each weight by the AS in the same cell. The TAS shows how attractive a strategy is considering only that one factor.

Step 6: Add up the Sum Total Attractiveness Score

Add the TAS values down each strategy's column. Higher is better. The size of the gap matters too: per the paper, the bigger the difference between the sums, the stronger the case for one strategy over another. The authors also note that the summed TAS is a better measure than the summed AS, because it accounts for the weights.

Worked example (hypothetical)

Let's use a made-up company, Harbor Foods, a regional meal-kit business. Everything below is illustrative and not real data. Leadership is weighing three strategies:

• A: open subscriptions in a neighboring city
• B: sell a retail version through grocery chains
• C: build an in-house delivery fleet

Using a 1 to 4 scale, no repeated scores in a row, and weights that sum to 1.0 on each side, the QSPM looks like this:

Read it row by row. On the first row, strategy A scores highest because more subscribers in a new city is the most direct way to ride rising demand. On the limited-cash row, B scores highest because shelf distribution needs the least upfront spend. On the logistics row, C scores highest because it's the only option that fixes the weakness.

What the result says

Strategy C is clearly last at 4.45. Strategies A and B are separated by just 0.10 (5.85 against 5.75). That's a close call, and a good moment to be cautious.

Test it. Suppose the team decides delivery fees are a bigger threat than grocer kits and moves 0.10 of weight from the grocer row to the delivery-fee row. Strategy A drops to 5.65, B rises to 6.05, and C rises to 4.55. The ranking between the top two flips. That doesn't mean the QSPM failed. It means the top two are roughly tied on this evidence, and the decision should turn on things the matrix doesn't capture: cash timing, management bandwidth, and what you can reverse if you're wrong. If cash allows, running A and B in sequence may be the real answer.

QSPM template

Copy this into a spreadsheet. Rows are the factors from your EFE and IFE matrices, and each strategy gets an AS and a TAS column. Use a dash in both columns when a factor doesn't affect the choice.

The TAS formula for each cell is weight times AS. The bottom row adds the TAS cells in each strategy column.

QSPM examples by business function

The QSPM started in corporate strategy, and David's 2016 paper argues for using it in marketing too. The same structure works anywhere you have a few strategies and a shared set of factors.

• Corporate strategy. A diversified firm compares market development, product development, and a joint venture, using factors from its EFE and IFE matrices. The Ansoff matrix is a good source of candidate strategies.
• Marketing. The 2016 paper builds a QSPM for a chain of ten restaurants choosing between raising advertising spend by 50% and cutting menu prices by 10%. It's a small, two-option example, and it shows the tool doesn't need a boardroom-sized decision.
• Sales. A sales leader compares three go-to-market moves, such as adding inside sales reps, opening a partner channel, or entering a new segment, against factors like competitor pricing, rep capacity, and pipeline coverage.
• Operations. A COO compares insourcing, outsourcing, or automating a process, scored against cost pressure, labor availability, and in-house skills.
• Human resources. An HR director compares building a graduate program, hiring experienced talent, or acquiring a team, against the talent market and the company's training capacity.
• Finance. A CFO compares funding a growth plan with debt, equity, or retained cash, scored against interest-rate conditions, investor appetite, and current leverage.

For choices that sit outside strategy and have no EFE or IFE behind them, a plain decision matrix is lighter and usually enough.

Limitations of the QSPM

The tool is useful, and it's also easy to over-trust. The numbers look precise, but they sit on top of opinions.

• It requires judgment. David's 2016 paper says the QSPM always requires intuitive judgments and educated assumptions. The weights, ratings, and ASs are judgment calls, even when they rest on facts, data, and trends.
• It's only as good as its inputs. The same paper says the QSPM can be only as good as the prerequisite information it's based on. A weak EFE or IFE produces a confident-looking ranking of the wrong thing.
• Close totals settle nothing. When sums are within a hair of each other, the matrix is telling you the options are similar. Run the weights again with a plausible alternative, as in the example above.
• It compares only the strategies you list. If the best option never made the top row, no score can find it.
• It ignores cost, risk, timing, and reversibility. A strategy can score well and still be unaffordable, or hard to undo. Add those judgments outside the matrix.
• Scores can drift toward a favorite. If the team already wants strategy B, the ASs will quietly bend toward B. Have someone who doesn't own a strategy challenge the scoring.

QSPM dos and don'ts

Do

• Build the EFE and IFE matrices first. The QSPM borrows their factors and weights directly.
• Use specific, quantified factors and strategies. Numbers and named actions force clearer thinking.
• Score row by row, with no repeated numbers in a row. It forces you to separate the options on each factor.
• Use dashes honestly. If a factor doesn't affect the choice, leave it out of the arithmetic for that set of strategies.
• Test the result. Move a weight or two and see whether the winner changes. If it does, treat the top options as tied.
• Have several people score independently, then compare. Disagreements point to the assumptions worth discussing.

Don't

• Don't change the weights to get the answer you want. The weights come from the input stage.
• Don't compare strategies that aren't mutually comparable. Strategies that can all be done together may not need ranking at all.
• Don't read 5.85 against 5.75 as a verdict. A gap that small is a tie.
• Don't skip the matching stage. A QSPM with no systematic strategy generation is a ranking of whatever someone wrote on a whiteboard.
• Don't treat the output as the decision. It's an input to the conversation.

Learn more

• EFE and IFE matrix: how to build the weighted factor lists the QSPM relies on.
• IE matrix: a matching-stage tool that places divisions on a nine-cell grid.
• TOWS matrix: generate the strategy options you will feed into the QSPM.
• SWOT analysis: where many of the factors come from.
• Decision matrix: a lighter weighted-scoring tool for choices outside strategy.
• BCG matrix: another matching-stage tool for portfolio decisions.