Towards a Suburban Renaissance

How lessons from Croydon can be applied to London’s suburbs to deliver thousands of new homes through modest intensification.

“Boroughs should…recognise in their Development Plans and planning decisions that local character evolves over time and will need to change in appropriate locations to accommodate additional housing provision and increases in residential density through small housing developments.”

Draft London Plan, December 2017

I live in suburban north London, in a neighbourhood which sprang from almost nothing in the late nineteenth century with the arrival of the railway. New Barnet station is at the end of my road and my house was built on land previously bought by the railway company: we still have the original deed of transfer from 1899 which details the sale of our plot from the railway company to the developer who bought it and built the home in which I now live.

New Barnet in 1897. The railway arrived in 1850 when farmland was acquired by the Great Northern Company to enable the construction of the route, and then the land around it was sold to the British Land Company (image from National Library of Scotland).

The streets here are largely lined with Victorian terraces, with some grander villas dotted around on larger plots. Sprinkled among these are houses and flats built in the later years as a result of incremental intensification, some on the former gardens of the bigger homes, others on the site of houses destroyed by bombs in the Second World War. : There’s a handful of more recent interventions: nearby, a backland site turned into eight contemporary houses which, of course, Theresa Villiers—our local MP (for the time being)—objected to, and so on.

A typical suburban neighbourhood with deep rear gardens and lots of parking. Most of this area is less than 10 minutes’ walk from New Barnet Station (Google Maps).

Let’s Take a Ride…

Although we’re in Zone 5, trains run into town in less than half an hour; to Moorgate via Finsbury Park and Old Street, and recently our line has been connected to Thameslink, with peak-hour trains connecting commuters with the Elizabeth Line at Farringdon and on to southeast London. It’s a convenient place to live.

But, having said all of that, New Barnet—and other parts of suburban London just like it—simply aren’t that dense. Pockets of new development have been snuck into redundant land, former garages and car parks, derelict pubs and disused warehouses, and even so, the most recent Census data from 2021 tells us that the density of this part of north London is just 18 dwellings per hectare (dph). Maida Vale, as a comparison, has a density of more than five times that. And Maida Vale is hardly somewhere you could describe as an unpleasant place to live.

Whichever way you look at it, suburban London can clearly do more to meet the city’s housing needs.

The shortage of housing in London is at crisis levels and manifests itself in many ways. Young people have been particularly badly hit, and the consequences for our economy and society are dire. In Hackney, schools are closing because young couples are unable to afford to start families. Homelessness is at record levels, with one in ten children in parts of London classed as effectively homeless. Median house prices in the capital are now 14 times average incomes while wages have stagnated. While this cannot be entirely blamed on our inability to build enough homes, it certainly plays a very large part.

Land in London is precious, yet the suburbs have a hegemony over it. Those lucky enough to own a house in the suburbs and, in particular, those living close to public transport, surely have a moral duty to allow more housing to be built around them so that others can benefit from convenient access to all of the amenities that the city has to offer.

So where might these houses go? Do we have the space? And how can we encourage intensification to happen?

Diminishing Ambitions

The current Mayor of London’s strategic plan for the city, the “London Plan”, was finally adopted in 2021 it set ambitious targets for new homes across the city, compelling each of the planning authorities to meet specific annual housing targets both, with a proportion of these to be delivered on small sites, that is any plot with an area of less than 0.25ha (about a third of a standard football pitch).

An early consultation version of the Plan was accompanied by a series of policies which provided a framework for intensification, clearly stating that boroughs needed to accept that “local character evolves over time” and that it would “need to change in appropriate locations to accommodate additional housing provision”.

I’ve written elsewhere about the push-back from many of the outer-London boroughs to this policy which resulted in the final version eviscerating the small sites targets, and Croydon’s progressive attempts to densify suburban areas that were unceremoniously chucked out by an incoming NIMBY mayor. But even in the short period of time that Croydon’s policy was in place, it resulted in a remarkable outcome, delivering around 2,000 homes within developments of fewer than 10 homes, with house prices and rents levelling off as a result.

So, what if the lessons from Croydon could be repeated across the rest of suburban London? That’s what I’ve set out to establish.

It’s about to get a bit geeky from here on in.

Cum On Feel The (Voro)nois

Using a combination of data from Ordnance Survey and Greater London Authority, I assembled a map of London and marked on it every station in the city – both Underground and mainline stations. Many stations are within 800m of each other, so I created Voronoi polygons to establish the closest station to every area in London.

Around each station I created an 800m diameter circle, which equates roughly to a ten-minute walking distance. By combining the two geometries I established the closest station to every area in London that’s no more than ten minutes’ walk away.

Clearly this approach doesn’t take into account the various constraints on potential development, including lots of areas which would, of course, be impossible to build on. The Thames, for example, but also areas of protected land such as Strategic Industrial Land (or “SIL”) Locally-Significant Industrial Sites (“LSIS”), green belt and Metropolitan Open Land. There’s a discussion to be had about whether protecting any space close to stations is sensible, and whether golf courses and industrial land might be put to better use. But for the purposes of this exercise, I’ve excluded them; together with parks, gardens, sports pitches and any other type of open space. Given my focus on suburban areas, I’ve also excluded the “Central Activities Zone”, which covers central London. Further refinements exclude a buffer either side of national and regional roads, and existing railways.

The resulting map of London looks something like this:

So now that we have a map showing all of the potential areas that might be intensified around London’s stations, we need to introduce some data which tells us more about the neighbourhoods around them.

Census Sensibility

The 2021 Census provides a huge set of data broken down into geographic zones that enables us, with a bit of mapping jiggery-pokery, to intersect them with our areas of interest.

Using Census data broken down by Medium Super Output Area (MSOA) I divided the mapping areas by the equivalent polygon areas. First, though, I ran a series of mapping exercises to establish some additional figures for each of these regions: for example, using Ordnance Survey Zoomstack data to measure the approximate coverage of buildings for each MSOA polygon. Bringing the two together enabled me to examine each of these areas in more detail. Here’s an example: MSOA ref. E02000028 which is located immediately to the west of New Barnet station.

Measurements taken from GIS tell us that MSOA E02000028 has a total area of 105.61 hectares, and the census data tells us that this contains 2,783 homes (45% of which are detached or semi-detached houses) – an equivalent density of about 26 dwellings per hectare. The footprint of all the buildings is about 18.7% of the MSOA, which makes sense given the large rear gardens, even though there are no large areas of open space within it. The census also tells us that, with a total population density of 62 people per hectare, the occupancy level is only 2.35 people per dwelling…which is surprising given the number of very large houses found here (the highest dwelling occupancies in London tend to be in the East End, with parts of Bethnal Green exceeding eight people per home).

You can see the hatched areas overlaid on the image above, which represent the different Voronoi polygons described early. To the bottom right of the image you’ll find Oakleigh Park station, and this MSOA is divided into three sub-areas, each part closest to a different station: in addition to New Barnet and Oakleigh Park, the north-west corner is within 800m of High Barnet Underground Station.

26 dwellings per hectare is pretty low, although not untypical of suburban London. A modest increase over this area could result in a significant number of new homes – let’s imagine for a moment that this is increased by just 25% (hardly a transformative figure). Yet, even at these modest numbers this results in 686 additional homes – an uplift in density from 26 to 32 dwellings per hectare.

Even 32 dwellings per hectare is pretty modest when compared to other parts of London. MSOA E02000589 covers the area around High Street Kensington, topping out at 137 dwellings per hectare (dph). This is probably a bit much for Zone 5, but Herne Hill (MSOA E02000642) achieves a density of 40 dph and can hardly be considered overcrowded.

With all of this in mind, I’ve established a few rules to apply to my data to try and estimate what a modest uplift in density might achieve. Arguably, nowhere in London that’s within 800m of a station should have a density of less than 40dph, so I’ve set that as a minimum. And, although some parts of the capital exceed this, I suggest that the increase in density should not push an area beyond 100dph. Within these thresholds, I’ve set a few additional rules: where detached and semi-detached houses form more than 40% of the total dwellings, I’ve set the potential density increase at 50%; where they’re less than 10% of the total housing stock, it’s 10%. For everything else I’ve assumed a 25% increase.

I’ve made a further adjustment where buildings cover less than 25% of the available land, adding a compound increase of 40% to this figure. The resultant algorithm is something like this (where “familyHouses” means a semi-detached or detached dwelling):

# First, calculate the initial uplift in density based on the proportion of "family homes"

IF familyHouses > 40% THEN newDensity = existingDensity x 1.5
ELSE IF familyHouses < 10% THEN newDensity = existingDensity x 1.1
ELSE newDensity = existingDensity x 1.25

# Then add a compound density based on the total percentage coverage (footprint) of buildings over the MSOA area
IF coverage < 20% THEN newDensity = newDensity x 1.4

# Finally, if the new density exceeds 100 dph, cap the increase to this level (this means that any areas that already exceed 100dph see no increase)

IF existingDensity > 100 THEN newDensity = existingDensity
ELSE IF newDensity > 100 THEN newDensity = 100
ELSE IF newDensity < 40 THEN newDensity = 40

Applied across the entire city, this results in a net increase of some 900,000 homes, with each of the boroughs seeing the following uplift:

BoroughNet New Homes
Barking & Dagenham15,070
Hammersmith & Fulham9,755
Kensington & Chelsea5,537
Kingston upon Thames27,862
Richmond upon Thames31,589
Tower Hamlets11,633
Waltham Forest21,822

Unsurprisingly, those boroughs with the largest area see the greatest net increase in new homes, with Bromley at the top with 68,426 new dwellings, and Croydon slightly behind with 67,165. The inner London boroughs such as Camden, Kensington & Chelsea and Westminster see the least. The City of London is at zero and doesn’t appear in this table because it’s entirely within the Central Activities Zone and excluded as a result.

It’s important to remember that the figures I’ve listed above are limited to those areas within 800m of a station. That means there’s a lot of outer London excluded from my estimates, but imagine that we increase the density here as well, perhaps by a more modest amount…there would surely be many more thousands of homes that could be built in addition to the 900,000 I’ve suggested above.

Due to limitations in the mapping data, there are some anomalies which skew the figures in a few areas. For example, the Ordnance Survey mapping data doesn’t identify football stadia within its “sites” geometry, and while I’m ambivalent about the so-called beautiful game, and would be quite happy for every football stadium in London transformed into housing, I’m not sure Arsenal fans are quite ready for the Emirates Stadium to go the same way as their former ground just yet.

Using this methodology, the Emirates Stadium is identified as a location for intensification; Arsenal’s previous ground can be seen in the top right of the image, which was converted into homes after the club moved to its new location in 2006.

There’s also no adjustment made for those areas subject to wider regeneration schemes or empty sites. The large car park to the east of Stratford Westfield, which was going to be the home of London’s version of the Madison Square Gardens’ Sphere has an area of around 2.5 hectares and could feasibly provide 200-300 homes, but my methodology only shows an uplift of eight, as the density calculation is based on the entire MSOA area rather than this small section of it.

There are some other issues which could do with refinement. The MSOA boundaries do not take into account the type of space within them so, for example, with two polygons of equal size might have varying levels of undevelopable space. The total number of existing dwellings might be the same in both cases, and therefore the overall density would be shown as equal, however in reality the same number of homes could be crammed into a smaller area. This would mean that the impact of intensification would be more profound in the latter.

In reality, though, I’m not sure these anomalies make much of a difference overall as they seem to balance out across the wider picture.

So, these oddities aside, what does suburban intensification look like when applied to largely residential neighbourhoods?

Learning from south London

The troubled history of Croydon’s Suburban Intensification SPD is beyond the scope of this article (I wrote about its demise for OnLondon), but it really was the gold standard for how outer London boroughs might encourage development on small sites in residential areas.

The guide provided a series of simple diagrams which mapped out the evolution of suburban blocks to show how, over an 18-year period, infilling gap sites and the replacement of some large houses with a combination of flats and houses. Let’s take a look at these to see what this means in numerical terms.

The first extract, below, shows a typical suburban block of detached houses. In the top example (2016) there are 37 detached houses. Although the plan is supposed to be a generic example, it’s almost certainly based on a real part of Croydon. There are large rear gardens and gaps of varying widths between the houses themselves.

In the “evolved” condition of 2036, several of the houses have been replaced with new buildings, and some have had new homes erected in rear gardens. From this plan it’s impossible to count the new number of dwellings that might be delivered in this way (it’s not really the point of the drawing), but the drawing does attempt to show the subdivision of the new buildings into the individual demises. Assuming nothing is taller than three storeys, I count at least 50 new homes, including a mix of houses and flats—and 29 of the original houses remain. In total, that’s a doubling of density – and it can hardly be said that the character has changed beyond all recognition: the large rear gardens largely remain and the coverage of buildings relative to undeveloped space is minimal.

This demonstrates that the kind of intensification we’re talking about is entirely achievable, and any objection on the basis of unacceptable change in character is for the birds.

Such an approach is entirely possible if we’re prepared to implement to bold policy reforms needed to enable this kind of development to come forward. In the brief period between the Croydon SPD being adopted in 2018, and it’s unceremonious scrapping in 2022, there was a remarkable uptick in small site development across the borough. The GLA’s annual Housing in London report shows that during this time Croydon delivered (delivered, not just approved) nearly 2,000 homes within developments consisting of fewer than 10 homes: more than three times the next highest, Barnet.

It’s time to adopt a London-wide policy which encourages similar levels of development across all of London’s suburbs. We know we need the homes. We now know we have the capacity. Let’s get on and do it!

You can have a play with my online map showing all areas of suburban intensification by clicking the image below.


Small Sites, Big Ambitions

In comparison to other similarly-sized world cities, London is not very dense. With limited exceptions, such as Maida Vale, parts of Tower Hamlets and Kensington, much of the city has no more people per hectare than the satellite towns surrounding it. Arrive by train and this is only too apparent, with railways cutting through miles of two-storey Victorian terraces, only giving way to mansion blocks, high rise towers and high-density housing estates close to the heart of the city. Our housing is too thinly spread.

All land in London is a precious resource, and to sustain our capital’s economy and vitality we have to use it more effectively—and more fairly.

Living in any major city—and benefiting from all of the amenities and conveniences that it has to offer—comes with a moral responsibility to allow others to do the same. London’s suburbs in particular could do much more to help provide the homes that the city so desperately needs—no more so than in those areas which benefit from good access to the public transport network, and where reliance on private car ownership diminishes.

But in outer areas which have not been identified for large-scale regeneration, the process of intensification can be a tortuous one. Obtaining permission to build even a small development of new homes is disproportionately complex, time-consuming and risky when compared to larger strategic developments.

Yet, even within existing planning policies, all the tools exist to establish an environment where land seemingly lost to low-density housing can actually be reinvigorated through a process of gradual densification.

Focusing on areas within a ten minutes’ walk of the city’s suburban train and Underground stations, there is the potential for up to a million new homes to be built, surprisingly quickly and effectively.

When Mayor of London Sadiq Khan’s London Plan was adopted in 2021, it set out, for the first time, housing targets that must be achieved on small sites in each of the London boroughs, the City of London Corporation and two Mayoral Development Corporations. In this case, small sites were defined as anything with an area of less that 0.25 hectares—roughly a third of a standard football pitch. Accompanying these targets was guidance and policies on how such development should be encouraged through plan-making and decisions.

Although it didn’t become formal policy until 2021, Khan’s version of the Plan had first been published in draft form at the tail end of 2017. The boroughs either embraced or resisted the Plan’s ambitions largely depending upon their political persuasion at the time. Labour-run Croydon Council, on the southern edge of the Greater London area, was one of the first out of the blocks, quickly establishing a set of planning principles to be followed by applicants wishing to bring forward small-scale development in suburban areas—generally towards the southern border with Surrey. It’s award-winning Suburban Design Guide was adopted in April 2019, and provided clear parameters for the transformation of large, land-hungry houses into efficient, mid-rise developments. Essentially, as long as developers followed the rules established by the guidance, there would be no reason for their applications to be rejected. Some examples provided within the document demonstrated how, for example, a pair of adjoining large houses could be turned into as many as 20 to 30 new homes.

Extract from Croydon’s Suburban Design Guide.

Five years on from the adoption of the guidance, which was scrapped in 2022 by the incoming Conservative mayor, there is sufficient data to demonstrate the effect this policy had on housing delivery—and the figures are remarkable. In the four-year period between 2018 and 2021, Croydon managed to complete nearly 2,000 new homes on small sites within developments consisting of fewer than ten dwellings (noting that even this is below the London Plan’s small site threshold, which determines plot size but not the number of homes within it). The next highest delivering borough was Barnet, which in the same period delivered around a quarter of this figure.

The Suburban Design Guide neatly illustrated how larger areas of suburban housing could be intensified incrementally, resulting in a broader mix of smaller flats, townhouses and large family homes. This approach is borne out by the number of homes delivered in Croydon during a relatively short period of time: around 500 per year. There are 20 outer-London boroughs including Croydon. If the remaining 19 had managed to deliver housing on small sites at the same rate, we could have had another 25,000 homes built by now.

The Croydon experience provides a useful model for how suburban intensification might be achieved across the rest of the city. There are numerous benefits to this approach, in addition to the sheer number of new homes that could be delivered this way: smaller developments tend to rely more heavily on local supply chains, so can help reinvigorate local economies, providing jobs, skills and training. And, by reducing the barriers to entry through the mitigation of planning risk, developers are able to invest in better quality, more sustainable homes that meet local need—and significantly faster than large-scale housebuilding. The inclusion of policies which limit the net loss of family homes can also ensure that diversity of housing stock is maintained. 

Our research has shown that implementing a similar policy across the whole of London’s suburbs within 800m of a station could enable the delivery of between 850,000 and a million homes through a modest uplift in density of just 25%, assuming no lower than 40 dwellings per hectare (dph), and no higher than 100dph. Even at this modest level, which would involve limited disruption to existing communities, the potential gains are huge.

The recent investigation by the Competition Markets Authority into housebuilding identified planning uncertainty as a significant barrier to the delivery of a new homes, and in particular, to the entry of small-scale developers into the market, stating that there is “evidence that problems in the planning systems may be having a disproportionate impact on SME housebuilders.”

Providing certainty through the planning system has to be a key tenet of any drive to improve housebuilding. A strong presumption in favour of development close to existing stations in urban areas would help in this regard, backed by clear and unambiguous guidance on what types of development would be acceptable, including clarity on building heights, privacy distances, overshadowing and access to natural daylight, and so on. 

The 2017 draft London Plan stated that within close proximity to stations and town centres, “there is a need for the character of some neighbourhoods to evolve to accommodate additional housing. Therefore, the emphasis of decision-making should change from preserving what is there at the moment towards encouraging and facilitating the delivery of well-designed additional housing to meet London’s needs.” This text was expunged from the adopted version. Words to this effect should now be included within the National Planning Policy Framework, making an exception for areas protected by other heritage designations, such as conservation areas and proximity to listed buildings and so on. This direction should be accompanied by an instruction that local planning authorities develop clear design guidance to assist in the delivery of new homes on small sites. If they do not, then a default set of guidance should be established for applicants to fall back on until such time as this in put in place.

Suburban intensification is tricky, and alone will never be able to deliver all of the homes that the country needs. But experience from Croydon has demonstrated that when the right conditions are in place, it can be implemented quickly, and at scale. As the country recovers from a long period of stagnation, this is one way that we can not only build the homes we need—quickly, where they’re most needed—but also promote economic growth.


Procurement Using 50% Scoring Ratio

This describes a typical limited tender process using standard methods of price / quality measurement, with a pricing ratio set at 50%. It demonstrates that this scoring ratio will almost certainly result in the cheapest price winning the project, even with a very low quality score.

The sample scores used to test this model is as follows:

Bidder NameFee (£)Quality Score (Out of 100%)
Practice A 102,45082
Practice B78,00075
Practice C125,15085
Practice D98,50068
Practice E25,00025
Practice F107,00076

Note that the scoring for Practice E has deliberately been set very low, scoring just 25% for quality but also coming in at less than a third of the next cheapest bid. Unfortunately, such wild variations in price scoring are not unusual when bidding for public sector work. There are few other sectors where any sensible person would accept a tender which was so much lower than the broad average of others; yet, for architectural services, such low-ball bidding is common—and rarely rejected, despite the Public Contract Regulations allowing commissioning bodies to reject “abnormally low” bids. Given that architectural salaries are broadly similar, the only explanation for low fees is that the bidding practice is anticipating spending far less time working on the project than others. There are no innovations in the market which enable practices to significantly reduce the cost of delivering their services without reducing amount of time spent performing it, and therefore the quality of the design which derives from these efforts.

For the purpose of this exercise, the most expensive practice has also scored the highest for quality. This is useful to demonstrate how different scoring methods can achieve a reasonable balance between quality and price, delivering best value for the client.

The following sections explore different methods of scoring and, using the figures above, illustrates how different ratios and scoring methods result in very different outcomes.

Relative to Cheapest Method of Scoring

In our example, the lowest financial bid was £25,000, and the highest £125,150. Scoring was based on a quality / cost ratio of 50:50.

The highest quality score was 85% which, when adjusted to the quality ratio of 50%, results in a quality component of 42.5%.

Using this method of scoring, Practice E (the cheapest) is the winning bidder. Clearly, any practice securing work with a fee of less than a third of the nearest bidder is either going to be unable to service the project properly or will be making a significant loss. Nobody in their right mind would accept such a low tender from, say, a builder, as clearly the quality of the work would be commensurately poor. Yet this happens all the time when it comes to commissioning architectural services.

RankingBidder NameFee (£)Price Score (%)
(max. 50.00)
Quality Score (%)
(max. 50.00)
Total Score (%)
1Practice E (WINNER)25,00050.0012.5062.50
2Practice B78,00016.0337.5053.53
3Practice A102,45012.2041.0053.20
4Practice C125,1509.9942.5052.49
5Practice F107,00011.6838.0049.68
6Practice D98,50012.6934.0046.69

Out of interest, let’s test the same figures using an alternative ratio: 70% quality and 30% price. This gives us the following results:

RankingBidder NameFee (£)Price Score (%)
(max. 30.00)
Quality Score (%)
(max. 70.00)
Total Score (%)
1Practice C (WINNER)125,1505.9959.5065.49
2Practice A102,4507.3257.4064.72
3Practice B78,0009.6252.5062.12
4Practice F107,0007.0153.2060.21
5Practice D98,5007.6147.6055.21
6Practice E25,00030.0017.5047.50

This result isn’t ideal either, as now the most expensive bidder has won the day, with a quality score that’s only marginally higher than the nearest competitor, but a pricing score which is a fifth higher.

Perhaps this suggests that the relative to cheapest method of scoring is never the best one to use?

Relative to Best Method of Scoring

An alternative way of assessing quality is to award all of the available quality points to the best submission. Having established a shortlist of what are, presumably, the most capable qualifying competitors on the market, it is nonsensical that the cheapest price tender receives the full 50% of the price score, but the best submission does not receive the full 50% of the available points for quality.

It may be that assessors have already given the best submission the full available score for quality, but if not, this method assesses all quality scores relative to the maximum percentage available, as well as giving the maximum marks for price to the cheapest bid. In other words, the best quality submission receives the whole 50% available, with all the remaining scores calculated proportionately to this.

It goes some way to preventing the cheapest bid “buying” a project with an inferior submission accompanied by an abnormally low financial submission—but does it ensure that the client is receiving the best value for money?

In this example, and using the same 50:50 ratio, Practice E still wins, having scored 50.00% for price and 14.71% for quality. So, pursuing this method doesn’t seem to make much difference.

RankingBidder NameFee (£)Price Score (%)
(max. 50.00)
Quality Score (%)
(max. 50.00)
Total Score (%)
1Practice E (WINNER)25,00050.0014.7164.71
2Practice A102,45012.2048.2460.44
3Practice B78,00016.0344.1260.14
4Practice C125,1509.9950.0059.99
5Practice F107,00011.6844.7156.39
6Practice D98,50012.6940.0052.69

Mean Narrow Average Method of Scoring

The mean narrow average (MNA) method of scoring discounts the highest and lowest tenders, establishing the mean value of those that remain, and scores all tender prices against the closest to that mean value. Fee bids which are less than half, or more than double, the mean value receive a price score of zero.

With Mean Narrow Average scoring, bidders are compelled to identify the appropriate fee required to service the project rather than cutting prices to buy the job, which could lead to underperformance or claims for additional fees later in the programme. Excessively low—or high—fees are penalised.

For these pricing figures, the mean (average) bid, including the lowest and highest fee submission, was £89,350, and the median was £100,475.

The highest and lowest fee bids have been excluded when calculating the mean average.

Using Mean Narrow Average with a price ratio of 50% results in Practice A being the winning bidder. Intuitively, that seems like a reasonable result: Practice A scored very close the median score (there were two more expensive bids, and three cheaper ones), and scored second highest in terms of quality. The full rankings are as follows:

RankingBidder NameFee (£)Price Score (%)
(max. 50.00)
Quality Score (%)
(max. 50.00)
Total Score (%)
1Practice A (WINNER)102,450.0046.9141.0087.91
2Practice D98,500.0048.9634.0082.96
3Practice F107,000.0044.5538.0082.55
4Practice B78,000.0040.4237.5077.92
5Practice C125,150.0035.1542.5077.65
6Practice E25,000.000.0012.5012.50

Alternative Ratios

To test a few alterative scenarios, I’ve run the same figures as above, but using different price/quality ratios. In most cases, the outcome is the same: Practice A wins, right up to the point where price comprises just 10%. Then, the highest scoring quality submission—and the most expensive bid—is the one that’s successful.

This means that the use of Mean Narrow Average is probably best deployed with a quality/cost ratio of around 60% – 70%.

Quality: 60%, Price: 40%

RankingBidder NameFee (£)Price Score (%)
(max. 40.00)
Quality Score (%)
(max. 60.00)
Total Score (%)
1Practice A (WINNER)102,450.0037.5349.2086.73
2Practice F107,000.0035.6445.6081.24
3Practice D98,500.0039.1740.8079.97
4Practice C125,150.0028.1251.0079.12
5Practice B78,000.0032.3445.0077.34
6Practice E25,000.000.0015.0015.00

Quality: 70%, Price: 30%

RankingBidder NameFee (£)Price Score (%)
(max. 30.00)
Quality Score (%)
(max. 70.00)
Total Score (%)
1Practice A (WINNER)102,450.0028.1557.4085.55
2Practice C125,150.0021.0959.5080.59
3Practice F107,000.0026.7353.2079.93
4Practice D98,500.0029.3747.6076.97
5Practice B78,000.0024.2552.5076.75
6Practice E25,000.000.0017.5017.50

Quality: 80%, Price: 20%

RankingBidder NameFee (£)Price Score (%)
(max. 20.00)
Quality Score (%)
(max. 80.00)
Total Score (%)
1Practice A (WINNER)102,450.0018.7665.6084.36
2Practice C125,150.0014.0668.0082.06
3Practice F107,000.0017.8260.8078.62
4Practice B78,000.0016.1760.0076.17
5Practice D98,500.0019.5854.4073.98
6Practice E25,000.000.0020.0020.00

Quality: 90%, Price: 10%

RankingBidder NameFee (£)Price Score (%)
(max. 10.00)
Quality Score (%)
(max. 90.00)
Total Score (%)
1Practice C (WINNER)125,150.007.0376.5083.53
2Practice A102,450.009.3873.8083.18
3Practice F107,000.008.9168.4077.31
4Practice B78,000.008.0867.5075.58
5Practice D98,500.009.7961.2070.99
6Practice E25,000.000.0022.5022.50

Out of interest, what happens is we reverse the ratio to prioritise cost over quality, using the Mean Narrow Average scoring method? Well, here we go:

Quality: 20%, Price: 80%

RankingBidder NameFee (£)Price Score (%)
(max. 80.00)
Quality Score (%)
(max. 20.00)
Total Score (%)
1Practice D (WINNER)98,500.0078.3313.6091.93
2Practice A102,450.0075.0616.4091.46
3Practice F107,000.0071.2815.2086.48
4Practice B78,000.0064.6715.0079.67
5Practice C125,150.0056.2417.0073.24
6Practice E25,

Surprisingly (at least to me), Practice A still scores very highly, coming second to Practice D which had a similar, but slightly lower price, but the second-to-bottom quality score. Nobody in their right mind would advocate for the commissioning of architectural services based on such a skewed ratio, but this serves to demonstrate that our earlier conclusion that a quality ratio of between 60% and 70% is likely to yield the best outcome for everyone.

A combination of Mean Narrow Average (MNA) and Relative to Best scoring methods could also be used, i.e. where the price score is calculated as the MNA result with the highest quality score receiving all of the points available, but given the success of the simple MNA method, it’s probably unnecessary.

All of these figures have been generated using a live model which you can test with different figures of your choice, here. And if you’re a procurement officer or public client, try putting so real-life tender figures you’ve received into this too, and see whether the outcome would have been any different.


After posting this article on LinkedIn, I’ve been directed to a comprehensive analysis of the various pricing models available to the public sector, written by Rebecca Rees of Trowers & Hamlins, which sets these out far more comprehensively than I could ever hope to do.

You can download the document using the button below.