So: what makes us think it will be different this time?

 

It's a sad fact that so many fundraising/CRM database implementations fail or are not nearly as successful as we hoped. And although there are various potential reasons for this which are central to many of my blog posts, we can also look at this problem in another way - if you have experienced a failed project at your organisation in the past, then ask yourself this: If we are about to launch a brand new CRM procurement and implementation project, what makes us think it will be different this time?

If this strikes a chord with you and you want to ask this question internally at your organisation, then here are some questions you could consider and try to address. Hopefully, they will (at least start to) give you the ability to decide whether or not you have learned from previous projects and tell you a lot about yourselves before you embark on another big project.

• What were the reasons for failure on the last project? (Did we even hold a Lessons Learned meeting?)
• Did we even define success criteria? Were they measurable, achievable, realistic?
• Do we have a proper business case? Has it been ratified by more than just a couple of people?
• Are we asking the same people to run and be involved with the new project? If so, why do we feel they can now do it? Do they have that much better experience now? Do they know all the pit-falls they could encounter this time? Have we sent them on any sort of training or learning programme since?
• Have we got new people involved? Are they any better?! Do we need more people?
• Are our senior managers fully engaged?
• Do we understand what our risk is? Do we know how to mitigate or accept risk?
• How do we really know we have got an appropriate budget this time around?
• How do we really know our planned timescale is possible or realistic? Could it even be too slack?
• Do we have a project manager? What sort of experience do they have?
• Do we have project governance? Do we understand project governance?
• Even if we do feel we have learned lessons, how will we monitor the next project to make sure it stays a success?
• Was our actual data an issue? Do we have new faith in that now?
• How can we be sure that the next salesperson we meet doesn't spin us the same lines as last time?

As I said above, in some ways many of my blog posts encompass the above in specific areas or in more detail. So please do search for anything particular in my blog archive which might come out of your considerations. (And hopefully the links within the above list are a good starting point for other useful posts).

Maybe I can use a famous Albert Einstein quote to sum-up: "The thinking it took to get us into this mess is not the same thinking that is going to get us out of it."

Can End-Users Really Use Data Analysis Tools Without Data Experts?

There are some incredibly good end-user oriented data analysis software systems these days. Really user-friendly, lots of great graphical drag-and-drop functionality and one can get all sorts of analysis from them. Even the new CRM systems provide decent user-oriented tools which can be learned by non-technical staff in a comparatively short amount of time.

But herein lies the rub: if we make it so easy for end-users to be able to use what is actually quite sophisticated software, then how do we know they are using it correctly? Or more to the point: how do we know they are getting the correct data, getting the correct data which they really want, and interpreting the correct data correctly?

Let's take the simplest of examples: a user wants to know how many supporters they can mail for their next event. This means knowing how the database and data defines such supporters, knowing how to exclude deceased/gone-aways etc, knowing other opt-in and opt-out codes, knowing the opt-in and opt-out policies, knowing the meaning of the values within a specific field, knowing if other groups of users might want to approach the same supporters at the same time. And knowing exactly where and how all this is held in the database.

Maybe it isn't that easy after all… Add on any further level of complexity such as last raffle gift (not just any gift), average gift over the last 3 years, if they came or were invited to the same event last year, and you're starting to tax even the data experts.

Which is why so many charities have centralised, specialist data teams who do such work. Or at the very least, highly trained users in each fundraising team. With this approach, we can be sure that the specialists know not only the data and all the above conundrums but they also know what additional questions to ask the fundraiser who wants to know such answers.

All of which pains me a great deal to have to write. I want end-users to be able to run such queries themselves, I want them to be able to be empowered to ask 'what-if' type questions so they can see data patterns, I want them to be more self-sufficient so that it will help them and take some of the strain off the database team.

But to get such analysis software to a point where this is possible, to ensure the data is so easy to understand that anyone and everyone can do, to ensure that internal policies are fully understood - all that is not necessarily easy.

Which doesn't mean we shouldn't try to do it and it doesn't mean it can't be done. We just have to ensure that appropriate software and data and policy training is given to those who need to know - and probably to limit the sort of reasons for why they are doing it in the first place. i.e. As long as the users are doing such queries just to get rough counts, to get some idea of data, to be able to do a first data sweep of a data mining exercise, then I think that should be possible. But sadly I don't think even the best software in the world yet means that a end-user can do their own segmentation and create their own mailing files for their next big event. We still need the data specialists for that.

The new world of cloud storage - do you really need ALL your old data?!

Traditionally, when moving from one fundraising database to a new one, charities tend to migrate all their old data across - or very nearly all. Sometimes, small sub-sets of old or truly unneeded data may be left behind, but in the main, every single donation, communication, appeal record etc and every entity and every field is transferred as is to the new database.

Why? Well, understandably, fundraisers and marketing staff are worried about losing granularity of historic data, of not being able to do true and useful RFV calculations or similar analysis on summary fields, of not being able to look back at why someone responded to appeal X or came to event Y. And the thought of either not keeping their data in the most granular state possible, or even not transferring it at all, has been a complete anathema!

But recently, this is something which is being challenged. This is partly due to cloud CRM systems charging for extra storage, partly due to some performance concerns for complex processes on very large systems and partly to mitigate some of the risks and complications of data migration. And partly it is just good business practise to challenge such assumptions.

But Why?!
But just as pertinent a question for me is: Why - Why do you need ALL your old data? Really - why?! I mean, are you really going to look back at someone's communication history from ten years ago and want to see that a donor was sent a second letter because a particular acknowledgement letter didn't reach them first time? Do you really need to know that someone was invited to an event twelve years ago but didn't respond? I'm not sure if you do…

And although I completely recognise the need to keep a granular donation history for at least a set number of recent years (e.g. at least four years for gift aid claims), at what point are your fundraisers not going to use such data for segmentation and marketing analysis? Five years? Six maybe? In which case, do you really have to be able to see each individual donation for older periods as a separate financial transaction on your new system? Or actually, could a summary be acceptable? e.g. a summary by year/campaign/gift type/whatever is appropriate for you.

Of course, there are some data items you would definitely need to keep, such as first donation information, maybe upgrade details etc, but do you have to have more than that for donations over a certain age?

And if you do, if you have to or if your organisation is too paranoid not to keep such data, then maybe you can store it elsewhere for when (if!) it is needed. For example, a separate data warehouse, maybe a simple SQL Server database, even a separate marketing software system.

And what about any old data which you still have on your system but which almost no-one in your organisation trusts and so doesn't use anyway? Does that really need to be transferred? Really?! And data accuracy in general - just how good is it over a certain period anyway?

Or, Should we be asking, Why Not?
Now. One could of course ask why we shouldn't migrate all data and that's a fair question. Storage does cost but is it so much more? And contemporary systems are so much more efficient now than older systems, why shouldn't we have millions of records in our new database?

Well, maybe because more data does add extra data management, does add complexity when doing segmentation and reports/analysis, can slow down a system when running such processes, can make screens slower to load when they have lots of historic information, can make data migrations more complex etc etc.

I think it is an interesting challenge - one I encourage you to consider!