Tag Archives: grant allocation

What can we learn from OTF giving history – Part 3

ACTION AREA

As promised in the previous posts 1 and 2, I now turn to Action Area and related variables, in the goal of understanding OTF strategy better. Just to remind you OTF action areas are as the following:
Active People, Connected People, Inspired People, Promising Young People,
Prosperous People, and Green People. Those areas supposedly organize grant application under sub-umbrellas, and allow better comparison between applications and grant outcomes.

The first analysis that came to mind was to compare areas (across years and types of grants) in respect to the Total awarded amount and monthly dollars. Interestingly enough, there are significant differences (F***) in both the total amount received and in monthly support, as the following:

The chart above clearly shows a tendency to support in higher amounts for Active People projects against all other types. It also seems, however, that the most funded areas in general are Green, Promising, and Prosperous. Inspired, Connected, and Active are somehow clustered together in the second priority.

Moving forward, I analyzed the connection between Action Area and Type of grant. Here, as well, differences are prevalent:

  • 40% of the Capital projects are in Active people area, and 24% are in Inspired.
  • Grow is more equal, but Promising Young get 25% of funding, seconded by Connected with 20%.
  • Seed has an indefinite preference for Connected (25%), and all other areas get varying amounts in the neighborhood of 13-18%, besides Active which gets only 9%.

Looking at Action Areas in general, focusing on type of funding, it seems that:

  • Active: 64% Capital, and 20% Seed
  • Connected: 49% Seed, and 28% Grow
  • Green: 53% Seed, 41% Grow
  • Inspired: 39% Capital, 36% Seed
  • Young: 45% Grow and 45% Seed
  • Prosperous: 45% Seed, 34% Grow

All in all, OTF strategy is certainly not equal in the pots of money across areas, and shows a clear tendency to prefer certain areas over others especially when it comes to specific types of funding. Those may be the results of specific tendencies in applications (i.e. Active applications tend to be focused on Capital requests rather than Seed; or Grow projects are more relevant in Young and Green). However, this analysis cannot account for those explanations, as OTF published only awarded grant data, and not full application requests.

GRANT RESULT*

Regardless of the Type of funding, I was very curious to check out the frequent/prevalent Grant Results. Those who are more frequent certainly fall under at least one of the following category (if not all): selection committee favourites, OTF team favourites, most frequent in requests, most frequent in agencies/organizations need, significant elements in projects growth, significant in sector-wide stability and growth, capture/promise change and opportunity. You may add more reasons as you wish, and I am happy to include them here for the benefit of my readers.

So, here are the top nine (afterwards come all 3% or less):

It is clear that the first and foremost concern is: social isolation. This result is significantly prevalent than others, and this simply means that if your project is connected to this result, it will be wise to choose it (use discretion and caution here, and choose it only if really connected to your project).
Second in line are: physical activities and culture/heritage. My thinking is that these two are highly connected to social inclusion in this way or another, so we can say safely, that an application about bringing people together whether if for sports, arts, crafts, event, festival, social program, get-together, etc. is definitely going to get significant and positive attention in your favour. If you look at the rest of the list, you will easily see other variations of physical activity, social inclusion, and you will see it narrows down to children and youth.

In this case, I can clearly say there is an evident pattern to prefer projects that are focused on Social Inclusion, Group Activities, and more specifically projects that target youth, children, and suggest programming around culture/heritage and sports. This is not to say that most of the money goes to these areas, but undoubtedly, those results are the most frequently funded ones.

This analysis also shows the preferred result for each top area:

  1. Connected: People who are isolated have connections in their community (n=301, %=35)
  2. Active: Infrastructure for unstructured and structured physical activities (n=205, %=34)
  3. Inspired: Arts, culture and heritage have appropriate spaces (n=180, %=21)
  4. Young: Children and youth who are facing barriers develop strong emotional and social skills (n=165, %=19)

*inluding Ontario150

Next, I analyzed the four top frequently funded areas, to see if funding dollars are also different. Strangely enough, there are real differences and trends in the total amount funded and monthly dollars.

Total highest $ go to Infrastructure (makes sense) and Children/youth (unclear why or how it’s so different than isolated people in general). Highest total monthly $ go to Infrastructure (makes sense) and another version of Infrastructure (makes sense). All in all, again, when you are making an application, if you include the social isolation component, you have significantly higher odds to win.


It should be noted that I looked into two other variables: Population and Age. However, majority of the grants were awarded for “general populations” without any certain age limit (children over 12 yrs and youth comprise of about 30% of total Age; people with disability 15% of total Population Served).

That’s it for this post, I hope you enjoyed and learned. On my next post, I will wrap up the discussion and focus on major findings in this analysis in the goal of identifying better how OTF strategy works, and how you may improve you application in the next round.

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WHAT CAN WE LEARN FROM OTF GIVING HISTORY? PART 2

In my previous post, I provided general information in respect to OTF grant strategy. This info sheds light on giving amounts, favorite grant types, long term strategy, and in general makes some order in thousands of raw data information. When trying to understand better how exactly the grants are divided geographically, I was dealing with technological challenges including pricey software and limited sharing capacity.

[long story short: started using Tableau, which is highly friendly however I could not share and was able to analyze on the first 3 letters on postal codes; then switched to PowerBI, which is significantly less friendly and shareable (although limited in time)].

All in all, I will present here maps that show giving dollars and postal codes, and clearly show where the money goes, and how much. Not surprisingly, population concentrations get more attention and funds (in general), but if you are interested in a specific location – those maps can give you highly effective visualization of the data. I was surprised to learn that maps can shape my understanding better than any other graphs that I dealt with so far; so even if you are experienced with data analysis for years, you may still be pleasantly surprised to be suddenly aware of the potential insights you enjoy while using in data mapping.

Back to business, the map below shows average giving per month based on the postal code.
The range is between $2,125 and $265,883 per month. Quite wide (I did not control for type of grant in this map). Due to technological constrains, I could not share the interactive map with you; so I captured the core, and left the rest of the province outside this image. However, we can easily see that GTA gets attention, and interestingly the periphery gets higher amounts (the dark blue on the right is K0K ($166k), and the semi-dark blue on the left are N0G ($87K) and N0H ($81K). The two small areas in the middle of the map are L4R in the north with $190K and L3Y in the middle with $178K.

Moving forward, I created an interactive map for total giving amount across the province. In this case, you can explore the area of interest and see how much in total was awarded per postal code.

Seed – $ per month

Diving into Seed grants over the years, it seems that there are actual differences between postal codes. At a general glance, the core of Toronto/York Region area does not get too much Seed if any, and the average dollars per months significantly vary. This raises the question whether organizations in this area are well established and therefore need less Seed funding, or maybe OTF strategy proiritizes other areas that are less central. I do not have an answer for this question (OTF do not publish unsuccessful application data), but you should take this into account if you are planing to apply for a Seed grant.

The map shows that the most funded is Toronto Biennial of Art (M6P) with over $35,000 per month. The least funded on a mothly basis is St. Vincent de Paul Society of Kingston (K7K) with just under $550 per month.
I cannot describe in words how exciting it is to play with the data over the map, but unfortunately I could not share it online.
Over-time analysis shows a trend of growth in average monthly funding: from $5400 per month in 2015/16 to $5550 per month in 2017/18.

(Average duration for Seed is 11 months).

On PowerBI it looks much less informative, and I could not find a better way to present the very same data. Anyways, here it is for you to interact with the data of interest.

Grow and Capital geographic distribution

Capital across the province (per month):

In general, again, it seems that the core of Toronto/York Region is less funded than other areas. This requires further investigation, as it is not explained by this data why the core is funded less than the secondary tier. Maybe additional variables such as populations and action areas will explain better.

Grow GTA (per month):

This map again raises more questions than answers. Why the core is not represented? Why there are areas that are heavily funded? Postal codes in the middle of the map: L0K, L0H, L0B, L4A, L7K (all around $18,000 per month); Toronto in the areas of M+.
No clear picture of funding strategy comes up from this map.

The only explanation I have now is that postal codes are more dense in more densely populated areas; and this may create a biased visual of funding distribution. However, this does not provide an answer to the question of monthly awards; and does not provide a good answer why over years some areas get zero attention.

At this stage, until I find a better solution, or I get positive feedback about PowerBI maps; I have no plans to produce interactive maps for Grow and Capital. Please write me if you think this is beneficial.

However, regardless of maps the below presents a summary of monthly dollars. In my opinion this is a good guide if you have future plans to apply.

Growth in monthly funding is prevalent and significant

When I tested Grow and Capital – growth in funding is clear.

Grow monthly avg. in 2015/16 – $10,500; 2018/19 – $11,900. (average duration is 33 months).

Capital monthly avg. in 2015/16 – $12,900; 2019/19 – $15,300. (average duration is 8.5 months).

In other words, the average grants you may want to apply for next round (assuming no significant changes in the process) are as the following:

Grow for three years, for about $400,000; or Capital for 8 months, for about $130,000. If judging from the theoretical amount you may get -Grow falls way behind the maximum of $750,000, and Capital obeys the defined boundaries of $150K.

By this I will end the blog post for maps. In the next posts I will focus on
Action Area, Grant Result, Demographics, and Funding Dollars.

Please feel free to share, comment, and contact me for insights and ideas.
Thank you for reading!

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Grant Allocation and Management

In small family foundations, the prevalent question is “how can we do best with our investment?”. Similarly to the question about fund investments in stock and other assets. However, the big question of how to impact the most with the funds, may be answered quite decently when taking several aspects into account:

(1) applicant information: what information is collected from applicant, and how much information is usable. In other words, the secret of data collection in the first stage is the lean nature of the collected data. Ensure the information requested is highly relevant for the decision making process.

(2) clear guidelines: when the foundation is getting too many irrelevant applications and letters, this raises the question of clarity and accuracy of guidelines for applications. Hence, ensure the application guidelines are clear, presented and accessible on the website, and state shortly and clearly who are the typical applicants to be considered. Also, provide a clear timeline for application rounds and decision announcements.

(3) decent evaluation: the most important, yet frequently neglected aspect, is evaluation and understanding of the contribution impact. It is easy to donate for a cause close to one’s heart. However, grant making is not only about giving, but also about ensuring the investment is impactful and fruitful. By this, the foundation needs to create simple rubrics or other evaluation tools to allow continuous and clear reporting (quarterly and annually). The evaluation tool should also provide the opportunity to compare between funded projects, to assist in decision making for future donations. Those evaluation tools do not have to be too sophisticated, they can be smart enough to compare and extract information based on the criteria on the guidelines, and most importantly – measure and evaluate the match and achievement of the foundation’s vision.

(4) organized decision making: when all the above are accomplished, the foundation’s management team and board are able to make decisions quite easily and effectively. Whether it is about deciding who are to be included in the next round of applicants (i.e. section 1 and 2 – guidelines and applicant information) or what was the impact of the invested funds over the year, and how the projects are doing in comparison (section 3). The management team arranges all the information for the board, and the board makes efficient,  wise, evidence-based decisions to highly impact and use the funds in the most significant way to achieve the foundation’s vision.

 

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