One of the industries where I have worked a lot with data quality issues is at nonprofit organizations such as charities and other form of membership based organizations.
A general characteristic of such organizations is that they have databases with as many “customers” as huge global enterprises; however the number of employee records is only a fraction compared to those large companies.
So the emphasis is often not at creating well manned data governance organizational structures but implementing the best automation available in order to have optimal party master data management, where the parties involved are members and other roles played by individuals and companies with a common interest.
Many nonprofit organizations have several different fundraising activities going on at the same time. This means that real world individuals, households, organizations and their contacts are registered through different channels. The challenges of getting a “single view of customer” from the data streams created in these processes are discussed in the post Multi-Purpose Data Quality.
There are many nonprofit organizations working internationally. The often decentralized management structures in nonprofit organizations means that way of doing things will naturally be different between countries where nonprofits are operating. Also the differences in legislation and culture are important. Some examples related to how to exploit master data are examined in the post Feasible Names and Addresses.
When it comes to creating business cases for data quality nonprofits are basically of course not different from any other organization. The main goals are increased fundraising and lowering administration costs. As said, the low number of employees often leads to using technology. The low amount of money available often leads to using agile technology.
Taking for granted that almost all data quality issues are created at source, i.e. where human beings are involved to interprete information and transform them into data, did you observe
that there are less data quality issues in non-profit organizations?
My point here is that people entering data are usually paid for speed and not for quality. Since I assume that the personal engagement for the purpose is higher in non-profit organizations, does that in your experience have a positive impact on the initial data quality?
Looking forward to your remarks (and may be a follow-up blog post?).
Thanks for joining Axel.
Surely people working for nonprofits, paid or unpaid, are very dedicated to the cause and often go that extra mile.
However nonprofits usually have many ways of gathering data where the initial data entry is already done by someone else. List brokering is one example and getting data from telcos based on donations via the phone is another example.
Axel your point could it be true but also you will need a data quality strategy to avoid mistakes and to have good data quality in your systems.
Hi Henrik. I did some interesting work for Plunket here in NZ which is a very interesting not-for-profit. They had some interesting data quality issues as they had several different sets of people that they had to keep information on: consumers of their services (customers if you will), which includes babies; the care-givers of said babies; a vast number of volunteers; and donors. Interestingly these data sets have to be kept distinct largely for privacy reasons. When you consider that there is a significant overlap between these groups (many customers are also care-givers, who also volunteer and donate), that the information is maintained by many different groups and people, and that there is a very interesting cross-over between volunteers and staff, this can lead to interesting data quality issues. None of which are faced by a normal commercial business. Not-for-profit is indeed very interesting!
Nonprofit organizations can certainly benefit from data quality initiatives the same as any other organizations. As you mentioned, multiple fund-raising activities make it essential to keep the member-base clean to reduce mailing costs and marketing wastage. Also, a great point you made about many non-profits working internationally – another challenge to maintaining standardized data.
One of the nonproft organizations we work with was initially not maximizing the performance of its renewal and new membership marketing initiatives. The organization implemented a data cleansing solution as well as marketing analytics software to reduce the amount of time required to process data and quickly enable marketing initiatives.
In our experience with non-profits, there are numerous challenges to implementing a data quality technology that will work. In addition to those mentioned:
-High turnover rates of employees make data governance or MDM initiatives unrealistic and hard to implement
-While a technical solution can be more efficient for the staffing structure, it must also be more user-friendly as there is often less access to technical support
-Every charity has unique features and sometimes a homegrown organizational structure requiring a rather custom strategy for implementing data quality
Overall, we’ve found that helping to establish some processes and failsafes is a very valuable investment in time for a non-profit customer. Plus, choosing a solution that does not require a sophisticated technical lead on the client-side, but which can offer the same level of fuzzy matching quality – is key.
Thanks Doug, Larisa and Chris for adding in and providing some good examples of issues and approaches at nonprofits.
Hi Henrik, actually I’m working in a BI project with a NGO and data quality is a key success factor to me
reference link: http://www.cepis.org/upgrade/media/III_2011_arenascontreras1.pdf
Thank you so much for this link Diego. Very useful reading.