Shares for the future: how I find companies for my Decision Engine
An important part of his investing process, analyst Richard Beddard explains how an idea makes it on to the list of shares he’s confident will make money through thick and thin.
16th January 2026 15:00
by Richard Beddard from interactive investor
The inspiration for my Decision Engine came from many places. One was a story told by the psychologist Daniel Kahneman in his book Thinking, Fast and Slow.
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Beyond first impressions
Early in his career, Kahneman worked for the Israeli army. Tasked with improving the recruitment process, he replaced unstructured interviews with a questionnaire that elicited facts about individual candidate personality traits and required the interviewers to score the answers. Not only did this system pick better candidates, but having interviewed systematically, recruiters’ intuitions were sharper too.
Kahneman was trying to reduce bias in the selection process. We exhibit bias, for example, when we jump to conclusions, or ignore information that challenges our existing views, without really thinking things through.
In the recruitment situation, first impressions matter. If a candidate is confident and good-looking for example, these impressions might mask all manner of deficiencies. A more systematic approach inoculated the interviewer, at least somewhat, to this “halo effect”.
There are parallels with shares. We constantly read about singular leaders and killer apps, and we are captivated by the growth their companies generate. But we should also focus our attention on less celebrated details that could break an investment.
Scoring is not a panacea. Personality traits are slippery, and so are the qualities of companies, so they cannot be precisely quantified. There is much we do not know and cannot score.
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But scoring keeps our attention focused on the facts we think matter, and allows us to express our degree of confidence in them. I felt that would take me closer to what was really going on with shares, and make my investment process more transparent.
I told this origin story for the Decision Engine during a presentation a few years ago. The talk went well, and there were many questions afterwards. The question I remember most vividly, was the one that exposed a hole in my system.
One member of the audience asked how I select companies for the Decision Engine. The answer was not very systematically.
Since then, I have tightened things up a bit.
From idea to engine
I get most of the candidates for the Decision Engine by filtering financial data in ShareScope, an online subscription service for private investors. I look for businesses that have profited through thick and thin.
There is no guarantee that a prosperous company will continue prospering in the future, but past prosperity is a starting point. Decent track records give me something to analyse and compare future performance to.
To promote a share to the Decision Engine, I want a business to have grown revenue for at least eight years without spending more than it has earned in free cash flow on acquisitions. It should not have raised money by issuing lots of new shares or borrowing heavily. It will have earned decent returns on capital in terms of profit and cash flow.
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Other criteria interest me. I prefer the directors to hold meaningful amounts of shares so they have skin in the game, for example. But the most important thing is that candidate companies have grown under their own steam and made good profits.
ShareScope tells me there are currently 102 UK-domiciled firms listed in London that meet my criteria.
This is the pool I fish from. The 30 shares below are the fish I have landed. Having scored their capabilities, risks and strategies, I expect them to continue to prosper.
30 Shares for the future
Here is the ranked list of Decision Engine shares. I review the scores at least once a year, soon after each company has published its annual report. The price scores are calculated using the share price prior to publication.
Generally, I consider shares that score more than 5 out of 10 to be worthy of long-term investment in sizes determined by the ideal holding size (ihs%).
Hollywood Bowl Group (LSE:BOWL) has published its annual report and is due to be re-scored.
company | description | score | qual | price | ih% | |
1 | FW Thorpe | Makes lighting systems for commercial, industrial and public settings | 9.0 | 0.9 | 9.7% | |
2 | Howden Joinery | Supplies kitchens to small builders | 8.0 | 0.6 | 7.2% | |
3 | James Latham | Distributes imported panel products, timber, and laminates | 7.5 | 1.0 | 7.0% | |
4 | Bunzl | Distributes essential everyday items consumed by organisations | 7.5 | 0.7 | 6.3% | |
5 | Renew | Maintains and improves road, rail, water, and energy infrastructure | 7.5 | 0.6 | 6.1% | |
6 | Jet2 | Package tour operator and leisure airline | 7.0 | 1.0 | 6.0% | |
7 | Hollywood Bowl | Operates tenpin bowling centres | 7.5 | 0.4 | 5.9% | |
8 | Softcat | Sells software and hardware to businesses and public sector | 7.5 | 0.4 | 5.8% | |
9 | Solid State | Manufactures electronic systems and distributes components | 7.0 | 0.9 | 5.8% | |
10 | Churchill China | Manufactures tableware for restaurants etc. | 6.5 | 1.0 | 5.0% | |
11 | Auto Trader | Online marketplace for motor vehicles | 7.0 | 0.5 | 4.9% | |
12 | Oxford Instruments | Makes imaging and semiconductor manufacturing systems | 6.5 | 1.0 | 4.9% | |
13 | Bloomsbury Publishing | Publishes books and educational resources | 7.5 | 0.0 | 4.9% | |
14 | Advanced Medical Solutions | Manufactures surgical adhesives, sutures and dressings | 6.5 | 0.5 | 4.0% | |
15 | Anpario | Manufactures natural animal feed additives | 7.0 | 0.0 | 4.0% | |
16 | Focusrite | Designs recording equipment, synthesisers and sound systems | 6.0 | 1.0 | 4.0% | |
17 | Macfarlane | Distributes and manufactures protective packaging | 6.0 | 1.0 | 4.0% | |
18 | Porvair | Manufactures filters and laboratory equipment | 8.0 | -1.0 | 4.0% | |
19 | Volution | Manufacturer of ventilation products | 8.5 | -1.6 | 3.9% | |
20 | Cake Box | Cake shop franchise and sweet manufacturer | 7.0 | -0.1 | 3.8% | |
21 | YouGov | Surveys public opinion and conducts market research online | 6.0 | 0.9 | 3.8% | |
22 | Cohort | Manufactures/supplies defence tech, training, consultancy | 8.0 | -1.1 | 3.7% | |
23 | Games Workshop | Designs, makes and distributes Warhammer. Licenses IP | 8.5 | -1.7 | 3.6% | |
24 | Judges Scientific | Manufactures scientific instruments | 7.0 | -0.2 | 3.6% | |
25 | Keystone Law | Operates a network of self-employed lawyers | 7.5 | -0.8 | 3.4% | |
26 | Goodwin | Casts and machines steel and processes minerals for niche markets | 8.5 | -2.0 | 2.9% | |
27 | 4Imprint | Customises and distributes promotional goods | 8.0 | -1.9 | 2.5% | |
28 | Renishaw | Makes tools and systems for manufacturers | 6.5 | -0.6 | 2.5% | |
29 | Tristel | Manufactures hospital disinfectant | 8.0 | -2.2 | 2.5% | |
30 | Quartix | Supplies vehicle tracking systems to small fleets | 7.5 | -2.1 | 2.5% |
Click on a share's score to see a breakdown (scores may have changed due to movements in share price). Key: qual is the share’s score out of 9 for the three quality factors (capabilities, risks, and strategy), price is the price score from -3 to +1, and ih% is the suggested ideal holding size as a percentage of the total value of a diversified portfolio.
Richard Beddard is a freelance contributor and not a direct employee of interactive investor.
Richard owns many of the shares in the Decision Engine. He weights his portfolio so it owns bigger holdings in the higher-scoring shares.
For more on the Decision Engine and Share Sleuth, please see Richard’s explainer.
Contact Richard Beddard by email: richard@beddard.net or on X: @RichardBeddard
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