What is discovery and how it is accomplished? It’s easy to understand the business processes involved in fundraising and how they are used to maximize fundraising – especially on the face to face fundraising front. A “large purchase” requires a significant degree of interaction with a person. We like our fundraisers to talk to other people. Most of us track this in some fashion and have some basic metrics in place.
The science of identification focuses on which people are likely and have the capacity to give us money. The challenge is to determine what happens “in between” the various stages. How do we filter the list down to those individuals where we have a workable number that we can actually visit? At the macro level surveying, marketing studies and giving histories can do the initial filtering. Analytics have greatly enhanced the piece by adding elements of predictability into our scoring and database systems so at a minimum we have segments of people that we can target our activities.
What does a personal visit discover? How does the up-front investment in the analytics and initial research change the cost metric of the visit? How do we aggregate the cost effect over time and measure and report in a way that demonstrates how effective we are in our visits? How do we ensure we’re collecting and maintaining the right information? What is fixed and what stays the same?
Fundraising is about changing the inclination of the prospect – we can’t do a whole lot to change their capacity, other than by direct interaction where we can assess their capacity more accurately by listening and by direct observation. “Grandchildren taken care of”, hobbies, pastimes, vacations, cars, artwork and other items of these observations change capacity. Based on what we learn and what we know, how do we change inclination and how do we measure and report on this change?
The format of discovery meetings tends to be short, intentional and on their “turf”. We need to glean as much as we can during the visit on both capacity and inclination.
A strategy that can be employed here is to develop a pre-visit agenda for fundraisers that helps them to focus on what they need to accomplish as part of the meeting. This additionally can help focus on the data elements that are useful to get into the database after the meeting. Another tactic is to have a structured contact report form that helps fundraisings to collect information – coupled with a data cleanup strategy that informs staff of data elements that may be missing for assigned prospects – such as an email address or cell phone number.
All of these tactics help tie business process and activities in place that reinforce the need to build and maintain an appropriate and accurate amount of information in the database – that focuses on major gifts prospects.
You may need to make changes in job descriptions and in the performance planning in your organization around contact reports and data management responsibilities for fundraisers. In any case, expectations for activities and the metrics that support the activities should be clearly established from the onset.
All prospect pools should be clearly identified and defined, along with appropriate stages. A glossary of organizational standards is ideally agreed upon as part of the business processes. As staff changes happen institutional memory often fades. Clear documentation of definitions is critical for continuity. What do you mean by pipeline? What do you mean by proposal stage? Many of us occasionally hire “outside” the fundraising industry and these folks may not always understand our jargon. Let’s make sure we are teaching them in the same way.
Our systems are often designed in ways that don’t have an adequate ability to track movement of a prospect through the various stages. When a prospect movers from identification to qualification there isn’t always a time stamp that is retained over time. You’ll often need to do workarounds – a good place for this is in your data warehouse where you can take time series snapshots of where prospects were at a particular stage so you can track metrics such as the time it took to get from point a to point b, how this changes with particular pools of prospects and how this is different for different development officers.
The time differences are a subset of activity metrics and can help us analyze where there may be bottlenecks at various points in the pipeline. For example, is a particular fundraiser more of a “good friend” to a donor than a fundraiser who is more apt to make an ask? The clog in this particular point of the pipeline will be represented by donors who on average have a longer time differential between moving from whatever stage to solicitation. If we’re able to track the length of stages in the relationships you can then work in investigating the reasons where there need to be changes in direction.
A tactic here is to create a spreadsheet and do an audit of some of the various activities, look at the timeframes and determine how we’re going to track some of these timelines. Other tactics include clarification of stages, look towards a new system where these time differentials can be tracked, build metrics that focus on inclination such as RFM scores (recency, frequency), set goals for qualification with a checklist, engage research and attempt to optimize portfolios. Consider how you record all of these elements in your database – try to avoid using notes or unstructured text feels and instead utilize the coding structures and attributes that are in most fundraising systems.
It’s important to include the capacity of your team. You may need to invest in additional resources if you need to ramp up your discovery processes. This will have to be all encompassing and should include your “back room” folks and your frontline fundraisers. The data processes that support the fundraisers are critical – as are the activities the fundraisers do, and the data they feed back into the database. Neither one of these activities can take place in isolation. You need to have in integrated approach. Think about the number of discovery visits per giving officer, the conversion ratios from number of visits to realized gifts and other metrics that demonstrate behavior.
Prioritize leads with techniques such as wealth screening and engagement models and scoring. Many organizations have built internal scoring engines. Build a suspect library and utilize a “check-in and check-out” strategy for assignments. For example, if a suspect is assigned, and no activity happens within a __ day period, then that suspect should automatically go back into the pool. This helps to stop the “hoarding” of suspect because fundraisers are given a timed expectation of when and what activity needs to take place. Again, an example of how good metrics and tracking help to reinforce the desired actions by staff. Make discovery a public metric – organizations need to know which techniques and which people do this the best – make it a learning environment rather than a punitive or performance management approach.
All of this will likely need continual refinement. Algorithms will tend to change over time, particularly if your data quality was suspect at the beginning of the process. Staff will change and as new staff come in, job descriptions and expectations can be changed. However, over time the results will always be worth it. “If we don’t measure it – it won’t get done” – an adage we all understand. We may need to become more creative in how we measure, develop new types of metrics and new types of reporting if we’re to maintain our competitive edge.
His management experience includes: technology and information systems, software conversions, gifts and records processing/management, prospect research, document imaging, web sites, online programs, finance, investments, working with senior management teams, strategic planning, boards and committees and other duties that help organizations manage their fundraising, constituent engagement and sustainability.
Brian’s current role of Senior Vice President for Finance and Information Systems at the VGH & UBC Hospital Foundation started in 2008.
Brian worked previously at the University of Michigan and was responsible for managing the technological infrastructure, gift processing and records administration for the Office of University Development. This was in support of a $3.1 billion campaign with annual fundraising revenues of $250-$370 million. The database contained over 1,000,000 entities and over 184,000 gift transactions were processed annually.
Prior to that, Brian worked at The University of Toronto. The University’s $1 billion plus campaign was Canada’s largest and most successful philanthropic effort in higher education. The database of over 700,000 entities supported a large-scale decentralized advancement operation.
Brian also worked at a number of other institutions and businesses in the United States and Canada, where he gained knowledge and perspectives of managing in small, medium and large shops. This experience included multiple system conversions, website development, budgetary and financial responsibilities, operations management and more.
He provides consulting services in Canada, the United States, Asia and Australia, has written many articles, is a published author and speaks at conferences and through webinars. He was a founding board member of the Association of Advancement Services Professionals and a founding committee member of the BC Blackbaud Users Group.