Introduction

This is the Planning Quality Framework report for Council A030. It tells the story of the performance of the council's Planning Service taking account of:

Facts; real-time data on planning applications.
- Part 1 The Work Profile
- Part 2 The Outcomes
- Part 3 Potential Waste Work
- Part 4 Fees, Resources and Investment
- Part 5 Process
Opinion; what customers say about the planning service
- [section tbc]
Practice: how the service is delivered and goes about negotiating the best developments and outcomes
- [section tbc]

The report includes some bar charts, line graphs and boxplots (guide to box plots). In the line graphs your council is represented by the thicker coloured line and your 'trend' is the thick red line. The overall trend, the average trend of all your comparator group, is indicated by the thicker, darker grey background.

The report has individual sections which are useful but on their own don't tell the whole story. The real story emerges when different parts of the report are knitted together. For example, how many councils, in response to a performance culture based on speed and targets, have carried out expensive process reviews just to make quicker decisions, and fail to notice that they say yes more than their peers, create less waste and have happier customers? That is the essence of this report - a much more rounded story of what is happening and what direction things are heading in.

PART 1 - The Work Profile

This shows the volume of applications by type of development that your service handles, the fee income, and the trends in these measures over time.

1a Application counts

Purpose: Understanding the volume of applications for each type of development over submitted quarters

As a collective (all of the comparator group combined):

plot of chunk application_1a

1b. Application Counts/ Fee Comparator

Purpose: To understand how your work and fee income compares with your peers.

This is the count and fee income of applications received, grouped by development type. This is an 18 month figure:

plot of chunk application_counts

For review:

What is most of the work? For most councils it will be householder and minor applications.
Do the volumes look right? If not, could it be that data is missing? Check, in particular, that you and your peers are recording conditions in the same way.
Do your priorities, processes and practices reflect the variety / volume of the work? Could you standardise or streamline more of the routine work or allocate resources differently? Is project and improvement work targeted at the right things?

The same information as a table (averaged into a month). Note that there are two lines for each development type, one for the count and one for the fee:

dev	category	A030	A013	A032	A041	A042	A008	A045
advert	appcount	8	7	6	5	5	8	5
advert	avefee	133	102	135	133	128	128	129
cert	appcount	2	8	12	3	4	3	2
cert	avefee	265	198	123	111	113	247	315
condition	appcount	16	20	NA	10	NA	NA	NA
condition	avefee	90	71	NA	86	NA	NA	NA
heritage	appcount	2	2	2	2	2	2	1
heritage	avefee	0	22	0	0	0	6	618
householder	appcount	30	89	58	38	45	109	44
householder	avefee	152	143	149	147	140	125	162
majormajor	appcount	2	2	1	0	1	5	5
majormajor	avefee	26501	6922	20275	28005	9701	11002	11080
minor	appcount	29	30	28	26	22	54	30
minor	avefee	524	492	622	624	506	350	750
minormajor	appcount	4	2	4	3	2	9	1
minormajor	avefee	8003	5957	4972	9592	7112	3773	7320
NMA	appcount	4	0	1	3	1	NA	6
NMA	avefee	150	19	121	155	192	NA	135
prior	appcount	3	12	2	8	5	NA	13
prior	avefee	171	10	205	77	5	NA	39
use	appcount	4	6	9	9	8	13	9
use	avefee	413	316	346	366	351	313	559
notification	appcount	NA	7	0	NA	4	9	NA
notification	avefee	NA	106	168	NA	163	41	NA

For review:

Is your application and / or fee profile very different to your peers? Is this expected? Are they doing something differently? Are these the right councils to compare with?
Are your peers seeing more of a particular type of development than you? Again, is this what you'd expect? Is there something happening in other places you could learn from?
Do the applications / fees mix represent any risk? Does a large proportion of fees come from a small number of applications? Are you managing this risk appropriately ?

1c. Applications over time

Purpose: To understand how the counts of the various sorts of applications are changing over time.
This plot uses a sample set of 1000 applications so each council has the same count.

plot of chunk application_overtime

For review:

Is there a a rise or fall in the numbers of certain development types? Does this correspond with your fee profile? Have the changes to the permitted development regime had any affect?
Are there any surprises or new things happening? Is the 'market' moving in a particular way?
If there is a trend and it continues, how might this affect things? How will your fee profile change? Is your skills base going to need to change? Can you say anything about your fee profile over the next few quarters?
Have you 'geared up' or formed teams to do certain types of work? How might this affect things?

PART 2 - The Outcomes

This part of the report looks at how often applications are approved and refused.

2a. Approval Rates

Purpose: How often are you saying 'yes' to and how does that compare with other councils? plot of chunk unnamed-chunk-1

This is the same information broken out by development type. For every 1000 applications of all types that you decide, you refuse this many of each type:

type	A030	A013	A032	A041	A042	A008	A045
advert	6	0	2	7	3	2	2
cert	10	5	32	1	14	3	1
condition	9	0	0	0	0	0	0
heritage	1	1	1	3	0	0	0
householder	6	44	47	52	26	35	7
majormajor	2	0	0	0	4	0	4
minor	9	13	25	17	22	20	10
minormajor	2	0	2	1	0	1	0
NMA	2	0	0	0	0	0	3
prior	2	4	2	6	4	0	3
use	0	0	11	12	7	5	1
notification	0	0	0	0	2	1	0

For review:

What is the overall trend? Are you granting more permissions? How might these messages be relayed to stakeholders?
Do your approval and refusal rates differ significantly from your peers on a particular type of development? What might be happening elsewhere that you can learn from?
How does your refusal rate for different development types compare with your peers? Are any of your numbers significantly higher or lower than those in other councils, and if so, why might this be?

PART 3 - Potential waste work

This part of the report looks at how much work gets withdrawn and how much additional work results from the original application e.g discharge of conditions.

3a. Withdrawal Rates

Purpose: Rates of withdrawal are a 'waste' indicator. Where possible they should be reduced to near zero.

plot of chunk unnamed-chunk-3

This is the same information broken out by development type. Figures represent a count of withdrawn applications from the sample set of 1000 applications.

type	A030	A013	A032	A041	A042	A008	A045
advert	3	4	0	1	2	3	4
cert	6	11	1	3	1	1	0
condition	9	1	0	0	0	0	0
heritage	1	1	0	4	1	1	0
householder	19	53	1	14	6	42	2
majormajor	1	0	0	0	2	0	5
minor	24	20	4	10	21	29	11
minormajor	5	1	0	2	1	3	1
NMA	1	4	0	2	0	0	1
prior	3	17	0	9	12	0	1
use	7	4	0	5	6	5	1
notification	0	4	0	0	2	2	0

For review:

What is the overall trend ? Are you trying anything to bring rates of withdrawal down? Is it working? Are there particular categories of development that suffer more?
What are withdrawn applications costing you?* For most category of applications, the fee does not cover the cost of processing them. A withdrawn application represents a cost for processing the application to the point it is withdrawn, and then there is the potential for a 'free go' (see Part 3 - non-heritage zero fee applications). Is there anything to be done?
How does your refusal rate for different development types compare with your peers? Are any of your numbers significantly higher or lower than those in other councils, and if so, why might this be?
Why are applications getting withdrawn? How many occur at the request of the council? What do your developer community think?

3c. Zero fee applications

Looking at the work involved in processing potentially avoidable zero fee applications (excluding heritage and tree applications that you have to process with no fee).
Purpose: , Zero fee applications are another 'waste' indicator. Where you can do so you should be looking to reduce their numbers.

The first graph shows your zero fee trend over time in comparison with your peers.

The second graph shows the time cost in days to do applications without a fee. For every 1000 applications, you do this amount of work without a fee:

plot of chunk 3d zerofee This is a table of the number of days spent doing work without a fee. This is not a total for the year - it is for your sample set of 1000 applications so an annual value will be different.

dev	A030	A013	A032	A041	A042	A008	A045
advert	1	1	1	2	4	3	0
cert	2	5	32	2	6	1	1
condition	6	5	0	9	0	0	0
householder	40	107	76	75	95	108	17
majormajor	12	12	116	0	12	0	116
minor	59	62	34	41	82	37	37
minormajor	19	7	47	0	39	110	0
NMA	1	3	0	1	0	0	2
prior	0	54	0	34	0	0	0
use	6	1	9	19	27	3	0
notification	0	3	0	0	17	43	0

For review:

Why are we receiving applications without a fee for non-heritage and tree applications? Zero fee applications can follow previous withdrawns. can we do anything to bring these numbers down?
How does your refusal rate for different development types compare with your peers? Are any of your numbers significantly higher or lower than those in other councils, and if so, why might this be?

PART 4 - Fees, resources and investment

This part of the report looks at the investment value that development proposals represent, and how well matched the resources (FTEs) are to the volumes of work.

Purpose: The following 3 plots follow the same form. These plots are organised by when the application is received (not determined).

4a. Fees received per quarter

plot of chunk 3a fees

For review:

How is the market behaving? You already know your income from fees. This plot shows you how your peers are faring so to help you understand whether changes may be part of a trend.

4b. Headcount estimate

This is still in test !
plot of chunk 3b FTE

The 'FTE estimate' plot is based on PAS 2012 Benchmark data. From this we know the average amount of hours it takes the average council to process different types of application, for example, a householder application takes 9 hours.
The FTEs represented here include all planning staff involved in handling an application â€“ administrative, technical, planners. We take your applications counts, multiply that by the hours we know it takes to process an application, then derive a headcount of planning staff required to handle your current workload.

For review:

How does the FTE estimate compare to reality? What might account for any significant differences? You should compare notes with your peers and help refine our time allowances for each class of application (you can see the values we've used for your report at the end of the technical appendix)
What is the overall FTE trend? Does this correspond with the volumes of applications you are receiving (Section 1)?
What do these numbers tell you about the proper resourcing for your service? Are there opportunities to re-focus resources?

4c. Investment estimate over time

plot of chunk 3c investment

The 'Investment estimate' plot is based on the build costs for different types of development - these are just simplistic estimates for now and the plot is just here to illustrate the concept.
Estimated build costs means an estimate accepted by the local authority as being a reasonable amount that would be charged by a person in business to carry out such work (as per building control).

For review:

Development Investment - what are the significant messages? The investment value will represent a significant sum and will put a perspective on many decisions facing the service - each planning consent results in some form of inward investment.
What do the trends (rising, falling or stable) mean for your place? Is there any significance between this and fee income (e.g. considering future resources available)? Is there a significance regarding the FTE estimate, for example, are you resourced to handle a growing upward trend, or might you have to re-focus resources to account for a downward trend?

PART 5 - Process

This section of the report focuses on processing times - summarising how long the validation and determination of applications took.

5a. How much work is valid on day 1 ?

Purpose: Shows the proportion of applications received that can be worked on straight away.

plot of chunk unnamed-chunk-5

For your sample set of 1000 cases there is a delay while the cases are all declared valid. (applications that were valid on receipt should have a zero delay) This has been divided by 7 to give a total weeks of delay:

type	A030	A013	A032	A041	A042	A008	A045
advert	75	68	31	60	89	45	57
cert	24	35	28	20	58	19	24
condition	112	50	0	100	0	0	0
heritage	34	4	12	15	12	9	21
householder	429	811	274	303	312	464	361
majormajor	27	8	4	2	87	43	68
minor	612	367	187	303	475	406	596
minormajor	131	3	34	55	57	57	13
NMA	26	0	5	3	12	0	7
prior	10	32	5	21	6	0	96
use	98	59	37	84	89	60	227
notification	0	37	1	0	21	30	0

For review:

The proportion of applications that are invalid. Anything above your line on the graph is the %age of applications that are invalid on receipt. This represents avoidable time and cost to make them valid.
How do you compare with your peers? Is there anything you could learn from those achieving a higher proportion of valid applications?
What is causing invalid applications. Don't assume that invalid applications are the sole fault of the applicant/agent. Consider whether your validation procedures, processes , consistency and customer guidance are as good as they could be.
What are your applicants and agents saying? Look over Customer Feedback Section XXXX, is there anything in there that could indicate what the problem with validation might be (e.g. poor guidance, inability to contact a member of staff for advice, inconsistent advice).
Are particularly catgories of applications more likely to be invalid than others? Might there be a need for some proactive work with applicants, or better on-line guidance.

The next 3 datasets use 'Boxplots'. Boxplots allow you to see how much variation there is in a set of data - something that a single number like an 'average' doesn't show you. Click here for a quick and simple guide to boxplots.

5b. Days to make valid (+trend over time)

Purpose: Shows the number of days it takes for applications to be made valid. A box-plot displays a range of local_values (days here). If you can't see a line in the middle of the box plot then your median local_value is zero (that means that at least half of the applications received are made valid on the day they arrive which is good).

plot of chunk unnamed-chunk-6

For review:

The boxes represent a range of days. The range is the lowest and highest number of days it can take for the majority of applications to be made valid.
Are the heights of the boxes inconsistent e.g. up and down? The more erratic the picture, the more inconsistent and uncertain the picture for the customer.
Do any of the quarters stand out as particularly different (better or worse)?
Are the heights of the boxes getting smaller over time (taking less time) or taller (taking longer)? Have you taken any action that might be causing this to happen?
This represents avoidable time and cost to the council and applicants. It doesn't affect National Indicator statistics (the clock starts ticking once the case has been made valid). BUT it all adds to the customer's wait for a decision.

5d. Days from declared Valid to Decision issued (+trend over time)

Purpose: Shows the number of days between applications being declared valid and a decision notice being issued.

plot of chunk unnamed-chunk-7

For review: As previous box plot plus

Are the 8/13 week targets driving decision making times or do you driven by 'what is the ealiest I can issue the decision'? Narrow green/blue boxes clustered close to the 56 day mark are an indicator of target-driven decision making. A lower edge to the box indicates that decisions are issued early.

5e. Average days per type of development

Purpose: Shows the number of days between applications being received and a decision notice being issued.

dev	category	A030	A013	A032	A041	A042	A008	A045
advert	validation	6	14	5	10	7	11	9
advert	decision	53	65	55	52	41	60	58
cert	validation	7	8	2	7	7	9	6
cert	decision	55	58	43	46	29	45	60
condition	validation	4	3	NA	5	NA	NA	NA
condition	decision	86	105	NA	54	NA	NA	NA
heritage	validation	13	13	6	6	10	11	14
heritage	decision	87	86	57	68	50	79	85
householder	validation	10	9	4	4	5	6	6
householder	decision	55	63	55	54	39	51	54
majormajor	validation	14	10	5	0	20	10	9
majormajor	decision	120	136	121	112	84	108	120
minor	validation	13	13	6	9	14	11	12
minor	decision	72	85	70	79	55	78	66
minormajor	validation	18	16	6	10	11	9	13
minormajor	decision	106	154	81	141	89	125	98
NMA	validation	4	0	3	3	5	NA	2
NMA	decision	35	28	50	29	22	NA	27
prior	validation	1	6	2	5	1	NA	4
prior	decision	52	44	43	38	22	NA	39
use	validation	16	19	6	9	16	11	14
use	decision	62	96	64	63	49	72	65
notification	validation	NA	9	3	NA	3	2	NA
notification	decision	NA	41	34	NA	28	26	NA

Test

This section is under test. If your group took an equal share of all the development, and carried on processing it in the same way, how long would you each take compared to the average ? For every application we sum the difference between you and the mean for each category of development. Low is good.

plot of chunk unnamed-chunk-9

And broken down by type of development:

plot of chunk unnamed-chunk-10

For review:

How much difference is there between you and your peers ?
Are there particular categories that are worth looking at ? Note that the largest cumulative differerences are for the most common applications.

End

This is a draft report for the Planning Quality Framework. It is version 0.8 last changed on 2015-04-19. It was generated on 2015-04-19.