Juno, queen of the Roman gods, was worshipped under many titles, and each named a different power. As Juno Moneta she held a temple on the Arx, and Romans honored her as the goddess of counsel given before a decision.
Her second power sat under the same roof. From the third century BC, Rome's silver mint operated out of her temple, striking coins for roughly four hundred years. Moneta came to mean mint, and eventually gave us the word "money." The goddess of warning was also the goddess of where the money came from.
Product Managers (PMs) need both of Juno Moneta's powers in the same meeting. The portfolio review is where money and resources get allocated, and it is rarely where anyone issues the warning. A product line with strong revenue growth gets funded on the strength of that growth, and few people ask about the market behind it.
Your moving annual total (MAT) has climbed for two years since launch. Your VP of Portfolio Strategy wants to know whether the product line earns another year of investment: line extensions, new application data, and marketing spend. You suspect part of that growth came from a non-repeatable market opportunity, and you have no clean way to separate it from what your product earned through performance, distribution, and customer loyalty.
Revenue in life science tools blends the two signals. For example, a qPCR reagent kit can post 22% MAT growth because NIH-funded infectious disease work is flowing through core facilities, while its market share stays flat. Or, a western blot antibody line can grow 3% and still be the strongest asset in the portfolio, because it holds 60% market share in an academic niche no competitor can contest. Revenue tells two different stories, and neither says where the next investment dollar should go.
The problem the Directional Policy Matrix solves
The business problem is budget allocation. Every life science tools company has more product lines asking for lifecycle investment than it can fund. Ranked by revenue, those requests favor whichever product sits in the most generous market. Get the ranking wrong and you pay twice: you fund a line extension for a kit whose market may soon cool, and you underfund the product line that was quietly building a position a competitor can now take.
Shell's chemical businesses hit this problem in the 1970s, built the Directional Policy Matrix (DPM) to solve it, and published the method in Long Range Planning in 1978. The DPM replaces the single revenue ranking with two questions. How attractive is this market, regardless of us? How strong are we in it, compared with the competitors we actually meet? PMs usually answer the second question well. The first is the one most portfolio reviews skip.
How to build a DPM in three steps
1. Score the market as if your product did not exist. Score each product line on five or six market parameters. Treat an instrument and its consumables as separate product lines, since they often land in different places. Portfolio leadership should set one set of weights for every line on the chart; otherwise each PM weights toward their own line. Weights differ by business model: a consumables business weights switching barriers and adoption momentum above funding climate, and an instrument business, which depends on capital budgets, does the reverse.
| Market parameter | What to measure | Where to find it |
|---|---|---|
| Size and growth | Three-year category revenue trend | Segment reporting in public tools companies' 10-Ks; analyst reports, cross-checked against each other |
| Funding climate | Grant dollars in your customers' application areas | NIH RePORTER; biopharma R&D spend disclosures |
| Adoption momentum | Whether the method is gaining or losing users | PubMed publication counts by method term, year over year |
| Competitive intensity | Credible supplier count and list-price erosion | CiteAb supplier data for antibodies; distributor catalogs; lost-deal notes |
| Switching barriers | What it costs a lab to change supplier | Validated protocols, instrument installed base, customer interviews, or a grounded synthetic customer panel to draft hypotheses first |
| Margin structure | Achievable gross margin in the category | Your finance team; public competitors' gross margins |
Before scoring, define what a score of 1, 3, or 5 means for each parameter. For funding climate, a 1 might mean grant dollars fell more than 10% over three years, a 3 means roughly flat, and a 5 means growth above 10%. Multiply each score by its weight and add the results. Here is the qPCR kit example:
| Market parameter | Weight | Score (1 to 5) | Weighted |
|---|---|---|---|
| Size and growth | 20% | 4 | 0.8 |
| Funding climate | 15% | 2 | 0.3 |
| Adoption momentum | 20% | 3 | 0.6 |
| Competitive intensity | 15% | 2 | 0.3 |
| Switching barriers | 20% | 3 | 0.6 |
| Margin structure | 10% | 3 | 0.3 |
| Market attractiveness | 100% | 2.9 |
Reading the table: the category is still growing, so size and growth scores a 4. But infectious disease grant dollars are falling and new suppliers are entering, so funding climate and competitive intensity each score a 2. Weighted together, the market scores 2.9 out of 5, just under the 3.0 midpoint. The market is less attractive than the kit's 22% growth suggests.
2. Score your strength against named competitors. Use the same 1 to 5 arithmetic, scoring your product line and your two or three strongest competitors on accessibility, product performance, share of citations or installed base, win rate, and cost position. B2B International treats accessibility (routes to market, infrastructure, market knowledge) as half of competitive strength, and in reagents it is often the weaker half: a superior ELISA kit with no distributor in Asia-Pacific scores low no matter how it performs at the bench. The qPCR kit scores 3.4, behind Competitor A at 4.1 but above the midpoint.
3. Plot the lines and compare each quadrant with its sales trend. Market attractiveness sets how high each line sits, competitive strength sets how far right, and bubble size shows revenue. Split each axis at a score of 3.0, and treat scores between 2.5 and 3.5 as a judgment zone that needs the weight test in the FAQs.
| Market attractiveness | High | Develop offerFund only the specific gap holding you back, such as distribution or performance data, or exit. | InvestFund R&D, line extensions, and sales coverage to build and defend share. |
| Low | Evaluate or disinvestRationalize SKUs, move to distributor-only, or discontinue. | HarvestKeep new R&D minimal, protect margin, and use the cash elsewhere. | |
| Low | High | ||
| Competitive strength | |||
The qPCR kit's 22% MAT growth looks like a case to invest. Its scores (2.9 market, 3.4 strength) put it in the harvest quadrant, because its share is flat while the category grows: the growth is coming from a funding wave, not from the kit. The western blot line, growing 3%, scores 3.3 on market attractiveness (high switching barriers, healthy margins) and 4.5 on strength (60% share), so it lands in the invest quadrant. The fast grower should get less investment, and the slow grower more. Our example is deliberately clean: the fast grower and the slow grower swap places completely. Real portfolios rarely flip this cleanly.
What the quadrant cannot tell you
Each quadrant implies a pricing stance: maintain current pricing in the invest quadrant, protect margin in the harvest quadrant, and resist discounting in the develop offer quadrant. What no quadrant tells you is what price a customer will accept. Two ELISA kits in the same quadrant can face very different willingness to pay, because one is written into a validated pharma protocol and the other is a line item a postdoc can swap next month. The next post makes the case for a third axis.
Juno Moneta held two jobs on one hill: counsel before the decision, and the mint that paid for it. Most portfolio reviews split them, funding first and asking questions once a product line misses its number. The DPM puts the counsel back in the room, before the budget is spent.
Before your next portfolio review, score your top five product lines. If none changes quadrant from where revenue would have put it, you've confirmed your plan with evidence. If one does, you've found the conversation worth having.
FAQs
How do I score market attractiveness without repeating my sales team's optimism?
Sales optimism measures how well your reps close, which belongs on the competitive strength axis. For market attractiveness, accept only evidence that would still be true if your product disappeared tomorrow: category growth from public company segment reporting, grant dollars from NIH RePORTER, and the number of credible suppliers compared with five years ago. If a data point depends on your own pipeline, move it to the other axis.
How do I know if my weights are skewing the result?
Weights are judgment calls, so test them. Move 10 percentage points between two parameters and recalculate. Shifting 10 points from funding climate to size and growth moves the qPCR kit from 2.9 to 3.1, across the midpoint. When a small change in weighting moves a product line into a different quadrant, get better data on the parameter causing the swing before you decide: here, confirm whether infectious disease grant dollars are actually falling.
What is the minimum version for a small team to implement?
Pick the three parameters per axis your business model depends on most, and score your top five product lines in one afternoon. Swap the evidence sources to fit your customers: an IVD raw materials supplier selling to diagnostic manufacturers learns more from its customers' assay pipelines and regulatory approvals than from NIH grant data. A rough DPM that exists is more useful than a rigorous one that never gets built.
