“Change” may not be coming to Washington as fast as we expected a year ago. Yet at the grass roots level, in the technology realm, something is definitely happening, and its going to help the policy reform process. The same kind of democratizing, collaborative, open source/open content trend that has swept through nonprofit technology now is gathering momentum in local, state and even national government. That was my overall takeaway from taking part in the March 6 New England Gov 2.0 “Unconference” at the Harvard Kennedy School of Government. Even if you didn't attend, you can find a lot of notes and material here: http://gov20ne.pbworks.com/ or look for Twitter archives at #gov20ne.
About 250 of us gathered in Cambridge as part of a series of Gov 2.0 summits and informal conferences around the country initiated last year by O’Reilly (the publisher) and other partners. While I have followed these to some degree, this was my first outing. Read more about the national efforts here: http://www.gov2summit.com/. On the related blog, you can sign-up to be part of the nonprofit/public sector connection.
Feeling that my own work straddles the fence between nonprofit and public sectors, I wasn’t sure how I would feel or where I would fit in that day. Right at home: we had an energized mix of public officials, government technology policy staff, nonprofit policy advocates, community activists, software developers, and academic researchers and students. Judging by the conversations at this conference, those working in human services, policy advocacy and political activism need to pay close attention to what is happening here. The public and nonprofit sectors have a lot to learn from each other, they serve common goals, and progress around effective use of data and the web will be mutually reinforcing. “Data” was likely the biggest buzz word at the conference—open data, sharing data, collaborative data, mapping and visualizing data and so on. This being an unconference, it aimed to self-organized by interest and we started by everyone giving a three words introduction of their background and interest. (Mine way, “share data now.”) Looking at the wordle (word cloud) of those introductions, you can see that data and open information drew many to the conference. (Creative Commons credit to http://www.wordle.net/ for the "Gov 2.0 Camp New England ")
Federal, State and Local Government agencies sit on enormous repositories of data that traditionally gets collected as a matter of course for regulatory reasons. We have business, economic, environmental and other data that advocacy groups need to be more effective. It’s often there but hard to get one’s hands on.
We also have mounds of data extracted from nonprofit social services and educational organizations at tremendous cost of time and infrastructure. Busy staff collect data to satisfy public grants as much or more than private foundation grants. From my point of view, this data may start as your data, yet once it passes to the government, it becomes public data. It makes sense that this data—in aggregated, depersonalized, privacy-protected form—be available back as well for communities to learn from, make their own assessments and evaluations of success and effectiveness.
In the public sector, making public data public serves the general good. Elected officials can commission and use (or ignore, as they see fit) qualitative assessments for policy making. The Gov 2.0 trend represents a desire for transparency around that government policy research.
Meanwhile, social sector advocates and activists have learned a lot about mining data to assess trends, correlate results with demographic and other community factors, and press for results and changes. We are all collectors of data and measurers of outcomes. This experience outside the government is an accelerant that will drive change inside the government. Organizational staff and consultants may gripe about grant requirements, yet we are also increasingly using the experiences to improve our own strategies and organizational management.
Toward a policy of "Data Impact Statements"
What should we look for, expect and advocate for in these realms?
First, the public wants more, easier, fuller access to government data. Yet government agencies have old systems, have legitimate boundaries around confidentiality and privacy, and have tight budgets and overwhelmed staff these days with little room to build elaborate data reporting systems. How do we strike a balance?
Where government agencies collect data, and most do, we should expect increasing transparency about what will be collected, at what cost in agency staffing and in compliance time and cost for those required to submit the data, with what quality, with what expected use internal to the government agency, and with what return back to the public. A few years ago, when incoming Massachusetts governor Deval Patrick asked for testimony to his Transition Teams, I proposed the concept of a standard “Data Impact Statement.” Like an environmental impact statement, government agencies would need to file a statement in a standard, readable format on any new initiative that collected data—individual filings or anything else. The statement would list what was being collected; what privacy, confidentiality, or security concerns there were about it; a pre-emptive judgment of the likely quality of the data; and what provisions the agency planned to make to put the data in the public domain.
In the not so distant future, we should aim that reactive freedom of information lawsuits will fade in favor of proactive Data Impact Statements throughout government. By having Data Impact Statements, at least advocacy organizations and human services agencies would be able to review, comment on, and press for change on what was going to happen with data their communities would provide and what of use they would get back. Over time, we can move toward uniform expectations—and funding to back it up.
Second, we should press that the release of data follow emerging technical standards. Web sites with pages of information, even if searchable, are not the same as reusable, transferable data format. The data evolutionary trajectory goes from text on the web, to tabular data on web pages, to downloadable text or Excel, to XML and now to the emerging concept of RDFa. http://en.wikipedia.org/wiki/RDFa and http://www.w3.org/TR/xhtml-rdfa-primer/. This year’s new Drupal release, for example, will embrace RDFa as a standard for web services and data exchange. I suspect that other modern data and community oriented software will as well.
Helping people ask, "How would this look on a map?"
Third, where the average person might reasonably ask, “how would this data look on a map,” public data should be presented with geographic information right there for use. The Gov 2.0 conference gave interesting attention to opening up data for spatial analysis, using geographical based information in crises such as Haiti and Chile, and innovative light-weight open source software like Ushahidi for social mobilization and response.
Fourth, even in the midst of glaring global policy issues from health care to the economy to the wars, we should give some attention to reinforcing national leadership coming in the tech sphere. The Obama administration has taken a strong stand on the democratizing of public data. The http://www.data.gov/ web site is both a growing repository of data anyone can use in the policy making process as well as a sounding board for developing technical and policy standards. It is a welcome initiative and I part of the framework that makes the Gov 2.0 conferences so timely.
Let data inform the educational policy debates
Fifth, if data is flooding in to government and beginning to steam out, we need keep a steady eye on privacy and confidentiality issues. Protect privacy yet don't let it derail opening things up.
A good example is in the realms of education policy. Policy advocates want to be able to do their own refactoring of data on mandatory testing, the record of charter schools, programs to reduce educational inequality, and other elements of No Child Left Behind and its local equivalents. Often this data usage gets lost or delayed because of how long it takes to resolve legal issues around protecting individual student and teacher performance data. In this day and age, we should be able to keep individual data confidential and make aggregated data public. We should also be able to let public school systems and community-based youth jobs and enrichment programs securely exchange individual level student data where both sides agree, have signed appropriate agreements, and have family sign-offs as well. This is probably the single most recurring technology related demand from staff I work with on youth and alternative education programs.
Mobile and Social Media And the Gov 2.0 Trend
Sixth, there is better access to existing data and there is creating new data. In particular, an additional important trend is the use Web 2.0 and social media technologies to inform, energize and empower the public. At the conference, probably the most frequently mentioned example of local tech initiative was the local transit authority’s initiative to put realtime tracking of buses and other transit in the hands of the public. Yes, others may have started on this long before Massachusetts. Yet it has been remarkable how quickly local developers rushed to create mobile apps and all kinds of technology ideas have surfaced around the transit data. At one level, having this information helps busy people know whether they can grab that extra cup of coffee and therefore promote local business at a time when the state really needs it. At another level, it will also help transit and environmental activists really focus in on questions about which areas of the city get what kind of service.
As we learned at the conference, many local communities are experimenting with mobile phone-based systems that enable people and organizations to report problems, oversee responses, and work collaborative to improve services.
All these trends and more will also aid business planning and development. For the moment, the main learning and drive in the Gov 2.0 trend is collaboration and sharing among nonprofit and public sector technologists and policy makers. If you aren’t yet following this trend, you need to.
The announcement that GuideStar, Charity Navigator and others would be moving away from the 990 form as their primary source for assessing nonprofit performance raised a lot of interesting questions, such as "How will assessments of outcomes be standardized in a way that is not too subjective?" and "What will be required of nonprofits in order to make those assessments?" We'll have a chance to get some preliminary answers to those questions on February 4th, when NTEN will sponsor a phone-in panel discussion with representatives of GuideStar and Charity Navigator, as well as members of the nonprofit community. The panel will be hosted by Sean Stannard-Stockton of Tactical Philanthropy, and will include:
As my colleague Steve Backman fully explains here, here's been some fallout from this story for Microsoft. First, like Google and Yahoo!, Microsoft operates a search engine in China and submits to the Chinese governments censoring filters. They've kept mum on their feelings about the cyber-attack. Google's analysis of that attack reveals that GMail accounts were hacked and other breaches occurred via security holes in Internet Explorer, versions six and up, that allow a hacker to upload programs and take control of a user's PC. As this information came to light, France and Germany both issued advisories to their citizens that switching to a browser other than Internet Explorer would be prudent. In response, Microsoft has issued a statement recommending that everyone upgrade from Internet Explorer version 6 to version 8, the current release. What Microsoft doesn't mention is that the security flaw exists in versions seven and eight as well as six, so upgrading won't protect you from the threat, although they just released a patch that hopefully will.
So, while their reasoning is suspect, it's nice to see that Microsoft has finally joined the campaign to remove this old, insecure and incompatible with web standards browser.
I have kept Google Wave open in a tab in my browser since the day my account was opened, subscribed to about 15 waves, some of them quite well populated. I haven't seen an update to any of these waves since January 12th, and it was really only one wave that's gotten any updates at all in the past month. I can't give away the invites I have to offer. The conclusion I'm drawing is that, if Google doesn't do something to make the Wave experience more compelling, it's going to go the way of a Simply Red B-Side and fade from memory. As I've said, there is real potential here for something that puts telecommunication, document creation and data mining on a converged platform, and that would be new. But, in it's current state, it's a difficult to use substitute for a sophisticated Wiki. And, while Google was hyping this, Confluence released a new version of their excellent (free for nonprofits) enterprise Wiki that can incorporate (like Wave) Google gadgets. That makes me want to pack up my surfboard.
Ask most any developer what's the worst part of a software project and mostly likely you'll hear, “data conversion.” And what's most magical when working a project spec? “We're going to start fresh with new data.”
Reflecting back on the year gone by, clean or messy data migration definitely has a huge impact project success as a whole.
What makes the data migration part of a project so hard?
You look at old data on screen, in reports, or with tech specs. That's often all you get to look at before starting, and that's not enough to judge its true quality. You can't fully judge how well its going to work until you do real trials into the new system. And you can't really do that until you have that new system ready.
So here are painfully accumulated tips about data conversion. I'm writing this from the point of view of the “joint planning team”--lessons to both client and consultant/developer. And I'm not going to say which ones I have the most success sticking to. I'm doing this partly as therapy and partly as New Year's resolution. I promise to reread this myself on every new 2010 project.
Data conversion and the project plan
Do as much clean up as possible in the old system. The data will look familiar there, and staff who have to do it will be faster on the old.
Don't wait until the end. Put time in the schedule to for clean-up straight through the planning and configuration of the new. Reflect each decision about the new back to the old. Understand how you will get there and when the route can be opened.
It's often hard to reserve enough time for clean-up. Explore whether you can effectively use volunteers, interns, or temp staff to do routine clean up work instead of taking consultant project time to do it or burdening organizational staff beyond what is reasonable or essential for each side to do.
Data conversion and the budget
Here's a tough one: See if you take data conversion outside of the rest of the project estimate and work it as time and materials. That protects the consultant and focuses program manager attention on only doing as much as is necessary.
The fall-back choice is to allocate a specific, reasonable number of hours, say as a percent of the whole project, and agree that the consultant will do much and as best they can within that block of time, and no more.
Data conversion and "letting go"
A corollary to the last: Consider converting the essential top level stuff—the primary contact lists—and not all the historical details (all donation or membership history, services rendered, etc). The top level lists are often cleaner, easier to check, more essential, and less encumbered with old-to-new data structure changes.
For historical data you really do need, consider adding special new fields to summarize the old. For example, instead of importing an entire “trainings” history, can you live with aggregating “total workshops attended” for each contact? And remembering preferred training topics, how about just tagging the contact with “attended series A workshops” or “workshop B series”? You might be surprised how much headache this saves where the old data turns out not as clean as it now appears on screen.
Data conversion in stages
It frequently makes sense to plan on a data migration way station--a temporary clean-up and check-me database. It could be Excel, Access or something else that has strong query and reporting tools. Maybe all the status categories need to be remapped, or collected from three different current places. Maybe the notes field holds way more than notes and needs analysis
On the other hand, the new system may have fantastic clean up tools available, such as address correction and verification, or deduping. Maybe it specifically has importers for the old donor database you are moving form. Check them on sample data and use them where you can.
What about all the rest of the details of the old? If keeping the old system around does not incur licensing or hosting costs, why not just leave it up, frozen as an archive for historical data. Again, only convert what is really needed.
Data conversion and testing
Count on doing at least one trial conversion for staff to test before the day you go live. Once you have worked that into the plan, it makes sense to do it as soon as a trial version of the new software is up. Let folks test the new software with some real, existing data. It improves the testing and improves the data migration. And make sure you have put time on the calendar for that checking. Discovering gaps six months into a new system, say when quarterly or annual reports first have to run for real, really will mess things up.
Do have a series of benchmark queries to run on old and new system to quickly check results. For example, maybe the count of contacts by status group has to match exactly. Maybe the total dollar value of donations by year will not match 100% for this, that and the other reason. Make an agreement in advance, the new system will vary by as much as 3% earlier than the last two years.
Conversely, agree on a couple representative accounts you will use as a standard base line for checking the conversion. I remember one large scale donor management system with a huge master contact list mostly sparsely populated and just a handful with tons of details. Running overall lists just wouldn't cut it. Every step in the development process had to be run against one particular wealthy donor with a 28-page single spaced personal profile. Each new iteration of the software had to pass muster on him or it was back to the cubicles for us.
Data conversion documentation
Data conversions usually involve a lot of steps. List them out in a shared document and explain what each does. When you have a series of scripts that have to run, number them in order, like “step100_clear main contact table,” “step 200_import from spreadsheet xyz,” “step310_relink contacts table to database X_manual step,” step 315 _import from database x,” “step 400_run dedup query,” “step510_extract priority A people to excel and give to ED to check personally.” By putting that first step in there, you have already set things up for running the conversion process as a whole more than once. Get every step, manual or automated, in there. Consider counting by 10s at least so you insert more steps as you fine tune the overall process.
Use a shared Google doc or some other collaboratively editable document to hold the conversion steps. Even if your steps lean toward the technical, take the time to go through them collaboratively, understand what they mean, and sign off that this is the plan.
Data conversion therapy
Accept that data conversion has a therapeutic component. You can count on the staff person who is most impatient with the old system to miss data and procedures that don't show up exactly the same in the new. Hmm. My Tai Chi sensibility says maybe the framework is more meditation than therapy: it's all about grasping the essence firmly, remaining calm to find the path from the old to the new, and letting go of what you can.
And through it all, be reasonable and patient with each other. This means the organizational lead needs to look at the raw underbelly of the data and appreciate whatever is giving he consultant the most trouble. The consultant needs to sit with users and understand the consequences, workarounds, new ways of doing things if new data doesn't 100% line up with the old.
Data conversion sounds like such a mine field that you might ask, why would anyone ever agree to do it? Well, you often have to, to get the project at all. In addition, I have to say, data conversion does have a creative appeal. Its almost always unique. Unlocking old data is like unraveling a mystery. It requires real detective work. It requires knowledge of multiple systems, which takes time and experience to accumulate. If both sides agree to a reasonable plan, it is possible for all to find satisfaction and joy when the new reports line up with the old.
And speaking of the therapeutic and the meditative, just writing this has been both therapeutic and meditative for me. hope it helps you as well, and best wishes for the New Year.
Last week, I reported that Nonprofit assessors like Charity Navigator and Guidestar will be moving to a model of judging effectiveness (as opposed to thriftiness). The title of my post drew some criticism. People far more knowledgeable than I am on these topics questioned my description of this as a "sea change", and I certainly get their point. Sure, the intention to do a fair job of judging Nonprofits is sincere; but the task is daunting. As with many such efforts, we might well wind up with something that isn't a sea change at all, but, rather, a modified version of what we have today that includes some info about mission effectiveness, but still boils down to a financial assessment.
Why would this happen? Simple. Because metrics are numbers: ratios, averages, totals. It's easy to make metrics from financial data. It's very difficult to make them out of less quantifiable things, such as measuring how successfully one organization changed the world; protected the planet; or stopped the spread of a deadly disease.
I used to work for an org whose mission was to end poverty in the San Francisco Bay Area. And, sure enough, at the time, poverty was becoming far less prevalent in San Francisco. So could we be judged as successful? Could we grab the 2005 versus 2000 poverty statistics and claim the advances as our outcomes? Of course not. The reduction in poverty had far more to do with gentrification during the dotcom and real estate booms than our efforts. Poverty wasn't reduced at all; it was just displaced. And our mission wasn't to move all of the urban poor to the suburbs; it was to bring them out of poverty.
So the announcement that our ratings will now factor in mission effectiveness and outcomes could herald something worse than we have today. The dangerous scenario goes like this:
Charity Navigator, Guidestar, et al, determine what additional info they need to request from nonprofits in order to measure outcomes.
They make that a requirement; nonprofits now have to jump through those hoops.
The data they collect is far too generalized and subjective to mean much; they draw conclusions anyway, based more on how easy it is to call something a metric than how accurate or valuable that metric is.
NPOs now have more reporting requirements and no better representation.
So, my amended title: "We Need A Sea Change In The Way That Our Organizations Are Assessed".
I'm harping on this topic because I consider it a call to action; a chance to make sure that this self-assessment by the assessors is an opportunity for us, not a threat. We have to get the right people at the table to develop standardized outcome measurements that the assessing organizations can use. They can't develop these by themselves. And we need to use our influence in the nonprofit software development community to make sure that NPOs have software that can generate these reports.
The good news? Holly Ross of NTEN got right back to me with some ideas on how to get both of these actions going. That's a powerful start. We'll need the whole community in on this.
This is very good news. That overhead metric has hamstrung serious efforts to do bold things and have higher impact. An assessment that is based solely on annualized budgetary efficiency precludes many options to make long-term investments in major strategies. For most nonprofits, taking a year to staff up and prepare for a major initiative would generate a poor Charity Navigator score. A poor score that is prominently displayed to potential donors.
Assuming that these new metrics will be more tolerant of varying operational approaches and philosophies, justified by the outcomes, this will give organizations a chance to be recognized for their work, as opposed to their cost-cutting talents. But it puts a burden on those same organizations to effectively represent that work. I've blogged before (and will blog again) on our need to improve our outcome reporting and benchmark with our peers. Now, there's a very real danger that neglecting to represent your success stories with proper data will threaten your ability to muster financial support. You don't want to be great at what you do, but have no way to show it.
More to the point, the metrics that value social organizational effectiveness need to be developed by a broad community, not a small group or segment of that community. The move by Charity Navigator and their peers is bold, but it's also complicated. Nonprofit effectiveness is a subjective thing. When I worked for a workforce development agency, we had big questions about whether our mission was served by placing a client in a job, or if that wasn't an outcome as much as an output, and the real metric was tied to the individual's long-term sustainability and recovery from the conditions that had put them in poverty.
Certainly, a donor, a watchdog, a funder a, nonprofit executive and a nonprofit client are all going to value the work of a nonprofit differently. Whose interests will be represented in these valuations?
So here's what's clear to me:
- Developing standardized metrics, with broad input from the entire community, will benefit everyone.
- Determining what those metrics are and should be will require improvements in data management and reporting systems. It's a bit of a chicken and egg problem, as collecting the data wis a precedent to determining how to assess it, but standardizing the data will assist in developing the data systems.
- We have to share our outcomes and compare them in order to develop actual standards. And there are real opportunities available to us if we do compare our methodologies and results.
This isn't easy. This will require that NPO's who have have never had the wherewith-all to invest in technology systems to assess performance do so. But, I maintain, if the world is going to start rating your effectiveness on more than the 990, that's a threat that you need to turn into an opportunity. You can't afford not to.
And I look to my nptech community, including Idealware, NTEN, Techsoup, Aspiration and many others -- the associations, formal, informal, incorporated or not, who advocate for and support technology in the nonprofit sector -- to lead this effort. We have the data systems expertise and the aligned missions to lead the project of defining shared outcome metrics. We're looking into having initial sessions on this topic at the 2010 Nonprofit Technology Conference.
As the world starts holding nonprofits up to higher standards, we need a common language that describes those standards. It hasn't been written yet. Without it, we'll escape the limited, Form 990 assessments to something that might equally fail to reflect our best efforts and outcomes.
A few months ago, I blogged a bit about Google Wave, and how it might live up to the hype of being the successor to email. Now that I've had a month or so to play with it, I wanted to share my initial reactions. Short story: Google Wave is an odd duck, that takes getting used to. As it is today, it is not that revolutionary -- in fact, it's kind of redundant. The jury is still out.
If you haven't gotten a Wave invite and want to try it, now is the time to query your Twitter and Facebook friends, because invites are being offered and we've passed the initial, competitive "gimme" stage. They should be easier to find if you speak up. And, once you get there (or if you are there and don't know what to do), there are some excellent ways to start learning and playing, which I'll discuss below.
Awkwardness
To put Wave in perspective, I clearly remember my first exposure to email. I bought my first computer in 1987: a Compaq "portable". The thing weighed about 60 pounds, sported a tiny green on black screen, and had two 5 and 1/4 inch floppy drives for applications and storage). Along with the PC, I got a 1200 BPS modem, which allowed me o dial up local bulletin boards. And, as I poked around, I discovered the 1987 version of email: the line editor.
On those early BBSes, emails were sent by typing one line (80 characters, max) of text and hitting "enter". Once "enter" was pressed, that line was sent to the BBS. No correcting typos, no rewriting the sentence. It was a lot like early typewriters, before they added the ability to strike out previously submitted text.
But, regardless of the primitive editing capabilities, email was a revelation. It was a new medium; a form of communication that, while far more awkward than telephone communications, was much more immediate than postal mail. And it wasn't long before more sophisticated interfaces and editors made their way to the bulletin boards.
Google Wave is also, at this point, awkward. To use it, you have to be somewhat self-confident right from the start, as others are potentially watching every letter that you type. And while it's clear that the ability to co-edit and converse about a document in the same place is powerful, it's messy. Even if you get over the sprawling nature of the conversations, which are only minimally better than what you would get with ten to twenty-five people all conversing in one Word document, the lack of navigational tools within each wave is a real weakness.
Redundant?
I'm particularly aware of these faults because I just installed and began using Confluence, a sophisticated, enterprise Wiki (free for nonprofits) at my organization. While we've been told that Wave is the successor to email, Google Docs and, possibly, Sharepoint, I have to say that Confluence does pretty much all of those things and is far more capable. All wikis, at their heart, offer collaborative editing, but the good ones also allow for conversations, plug-ins and automation, just as Google Wave promises. But with a wiki, the canvas is large enough and the tools are there to organize and manage the work and conversation. With Wave, it's awfully cramped, and somewhat primitive in comparison.
Too early to tell?
Of course, we're looking at a preview. The two things that possibly differentiate Wave from a solid wiki are the "inbox" metaphor and the automation capabilities. Waves can come to you, like email, and anyone who has tried to move a group from an email list to a web forum knows how powerful that can be. And Wave's real potential is in how the "bots", server-side components that can interact with the people communicating and collaborating, will integrate the development and conversation with existing data sources. It's still hard to see all of that in this nascent stage. Until then, it's a bit chicken and egg.
Wave starting points
There are lots of good Wave resources popping up, but the best, hands down, is Gina Trapini's Complete Guide, available online for free and in book form soon. Gina's blog is a must read for people who find the types of things I write about interesting.
Once you're on wave, you'll want to find Waves to join, and exactly how you do that is anything but obvious. the trick is to search for a term "such as "nonprofit" or "fundraising" and add the phrase "with:public". A good nonprofit wave to start with is titled, appropriately, "The Nonprofit Technology Wave".
If you haven't gotten a Wave invite and want to, now is the time to query your Twitter and Facebook friends, because invites are being offered and we've passed the initial "gimme" stage. In fact, I have ten or more to share (I'm peterscampbell on most social networks and at Google's email service).
Meaningful shared data, like the Miles Per Gallon ratings on new car stickers or the calorie counts on food packaging help us make better choices;
But not all data is as easy to interpret;
Nonprofits have continually been challenged to quantify the conditions that their missions address;
Shared knowledge and metrics will facilitate far better dialog and solutions than our individual efforts have;
The web is a great vehicle for sharing, analyzing and reporting on data;
Therefore, the nonprofit sector should start defining and adopting common data formats that support shared analysis and reporting.
I've made the case before for shared outcomes reporting, which is a big piece of this. Sharing and transparency aren't traditional approaches to our work. Historically, we've siloed our efforts, even to the point where membership-based organizations are guarded about sharing with other members.
The reason that technologists like Marnie and I end up jumping on this bandwagon is that the tech industry has modeled the disfunction of a siloed approach better than most. early computing was an exercise in cognitive dissonance. If you regularly used Lotus 123, Wordperfect and dBase (three of the most popular business applications circa 1989) on your MS-DOS PC, then hitting "/", F7 or "." were the things you needed to know in order to close those applications respectively. For most of my career, I stuck with PCs for home use because I needed compatibility with work, and the Mac operating system, prior to OSX, just couldn't easily provide that.
The tech industry has slowly and painfully progressed towards a model that competes on the sales and services level, but cooperates on the platform side. Applications, across manufacturers and computing platforms, function with similar menus and command sequences. Data formats are more commonly shared. Options are available for saving in popular, often competitive formats (as in Word's "Save As" offering Wordperfect and Lotus formats). The underlying protocols that fuel modern operating systems and applications are far more standardized. Windows, Linux and MacOS all use the same technologies to manage users and directories, network systems and communicate with the world. Microsoft, Google, Apple and others in the software world are embracing open standards and interoperability. This makes me, the customer, much less of an innocent bystander who is constantly sniped by their competitive strategies.
So how does this translate to our social service, advocacy and educational organizations? Far too often, we frame cooperation as the antithesis to competition. That's a common, but crippling mistake. The two can and do coexist in almost every corner of our lives. We need to adopt a "rising tide" philosophy that values the work that we can all do together over the work that we do alone, and have some faith that the sustainable model is an open, collaborative one. Looking at each opportunity to collaborate from the perspective of how it will enhance our ability to accomplish our public-serving goals. And trusting that this won't result in the similarly-focused NGO down the street siphoning off our grants or constituents.
As Marnie is proposing, we need to start discussing and developing data standards that will enable us to interoperate on the level where we can articulate and quantify the needs that our mission-focused organizations address. By jointly assessing and learning from the wealth of information that we, as a community of practice collect, we can be far more effective. We need to use that data to determine our key strategies and best practices. And we have to understand that, as long as we're treating information as competitive data; as long as we're keeping it close to our vests and looking at our peers as strictly competitors, the fallout of this cold war is landing on the people that we're trying to serve. We owe it to them to be better stewards of the information that lifts them out of their disadvantaged conditions.
To break down that tweet a bit, @kanter is the well-known Beth Kanter of Beth's blog. @pearlbear is former Idealware blogger and current contributor Michelle Murrain, and Beth asked us, in the referenced blog post, to dive a bit into internet security and how it contrasts with internet privacy concerns. Michelle's response, offers excellent and concise definitions of security and privacy as they apply to the web, and then sums up with a key distinction: security is a set of tools for protecting systems and information. The sensitivity of that data (and need for privacy) is a matter of policy. So the next question is, once you have your security systems and policies in place, what happens when the the policies are breached?
Craft a Policy that Minimizes Violations
Social media is casual media. The Web 2.0 approach is to present a true face to the world, one that interacts with the public and allows for individuals, with individual tastes and opinions, to share organizational information online. So a strict rule book and mandated wording for your talking points are not going to work.
Your online constituents expect your staff to have a shared understanding of your organization's mission and objectives. But they also expect the CEO, the Marketing Assistant and the volunteer Receptionists to have real names (and real pictures on their profiles); their own online voices; and interests they share that go beyond the corporate script. It's not a matter of venturing too far out of the water -- in fact, that could be as much of a problem as staying too close to the prepared scripts. But the tone that works is the one of a human being sharing their commitment and excitement about the work that they (and you) do.
Expect that the message will reflect individual interpretations and biases. Manage the messaging to the key points, and make clear the areas that shouldn't be discussed in public. Monitor the discussion, and proactively mentor (as opposed to chastising) staff who stray in ways that violate the policy, or seem capable of doing so.
The Case for Transparency
Transparency assumes that multiple voices are being heard; that honest opinions are being shared, and that organizations aren't sweeping the negative issues under the virtual rug. Admittedly, it's a scary idea that your staff, your constituents, and your clients should all be free to represent you. The best practice of corporate communications, for many years, was to run all messaging through Marketing/Communications experts and tightly control what was said. I see two big reasons for doing otherwise:
We no longer have a controlled media.
Controlled messaging worked when opening your own TV or Radio Station was prohibitively expensive. Today, YouTube, Yelp and Video Blogs are TV Stations. Twitter and Facebook Status are radio stations. The investment cost to speak your mind to a public audience has just about vanished.
We make more mistakes by under-communicating than we do by over-communicating.
Is the importance of hiding something worth the cost of looking like you have something to hide? At the peak of the dot com boom, I hired someone onto my staff at about $10k more (annually) than current staff in similar roles were making. An HR clerk accidentally sent the offer letter to my entire staff. The fallout was that I had meaningful talks about compensation with each of my staff; made them aware that they were getting market (or better) in a rapidly changing market, and that we were keeping pace on anniversary dates. Prior to the breach, a few of my staff had been wrongly convinced that they were underpaid in their positions. The incident only strengthened the trust between us.
The Good, the Bad, and the Messenger
Your blog should allow comments, and -- short of spam, personal attacks and incivility -- shouldn't be censored. A few years ago, a former employee of my (former) org managed to register the .com extension of our domain name and put up a web site criticizing us. While the site didn't get a lot of hits, he did manage to find other departed staff with axes to grind, and his online forum was about a 50-50 mix of people trashing us and others defending. After about a month, he went in and deleted the 50% of forum messages that spoke up for our organization, leaving the now one-sided, negative conversation intact. And that was the end of his forum; nobody ever posted there again.
There were some interesting lessons here for us. He had a lot of inside knowledge that he shared, with no concern or allegiance to our policy. And he was motivated and well-resourced to use the web to attack us, But, in the end, we didn't see any negative impact on our organization. The truth was, it was easy to separate his bias from his "inside scoops", and hard to paint us in a very negative light, because the skeletons that he let out of our closet were a lot like anybody else's.
What this proves is that message delivery accounts for the messenger. Good and bad tweets and blog posts about your organization will be weighed by the position and credibility of the tweeter or blogger.
Transparency and Constituent Data Breaches
Two years ago, a number of nonprofits were faced with a difficult decision when a popular hosted eCRM service was compromised, and account information for donors was stolen by one or more hackers. Thankfully, this wasn't credit card information, but it included login details, and I'm sure that we all know people who use the same password for their online giving as they do for other web sites, such as, perhaps, their online banking. This was a serious breach, and there was a certain amount of disclosure from the nonprofits to their constituents that was mandated.
Strident voices in the community called for full disclosure, urging affected nonprofits to put a warning on the home page of their web sites. Many of the organizations settled for alerting every donor that was potentially compromised via phone and/or email, determining that their unaffected constituents might not be clear on how the breach happened or what the risks were, and would simply take the home page warning as a suggestion to not donate online.
To frame this as a black and white issue, demanding that it be treated with no discretion, is extreme. The seriousness and threat that resulted from this particular breach was not a simple thing to quantify or explain. So it boils down to a number of factors:
Scope: If all or most of your supporters are at risk, or the number at risk is in the six figure range, it's probably more responsible, in the name of protecting them, to broadcast the alert widely. If, as in the case above, those impacted are the ones donate online, then that's probably not close to the amount that would fully warrant broad disclosure, as even the strident voice pointed out.
Risk: Will your constituents understand that the notice is informational, and not an admission of guilt or irresponsibility in handling their sensitive data? Alternatively, if this becomes public knowledge, would your lack of transparency look like an admission of guilt? You should be comfortable with your decision, and able to explain it.
Consistency: Some nonprofits have more responsibility to model transparency than others. If the Sunlight Foundation was one of the organizations impacted, it's a no-brainer. Salvation Army? Transparency isn't referenced on their "Positions" page.
Courtesy: Some constituencies are more savvy about this type of thing than others. If the affected constituents have all been notified, and they represent a small portion of the donor base, it's questionable whether scaring your supporters in the name of openness is really warranted.
Since alternate exposure, in the press or community, is likely to occur, the priority is to have a consistent policy about how and when you broadcast information about security breaches. Denying that something has had happened in any public forum would be irresponsible and unethical, and most likely come right back at you. Not being able to explain why you chose not to publicize it on your website could also have damaging consequences. Erring on the side of alerting and protecting those impacted by security breaches is the better way to go, but the final choice has to weigh in all of the risks and factors.
Conclusion
All of my examples assume you're doing the right things. You have justifiable reasons for doing things that might be considered provocative. Your overall efforts are mission-focused. And the reasons for privacy regarding certain information are that it needs to be private (client medical records, for example); it supports your mission-based objectives by being private, and/or it respects the privacy of people close to the information.
No matter how well we protect our data, the walls are much thinner than they used to be. Any unfortunate tweet can "go viral". We can't put a lock on our information that will truly secure it. So it's important to manage communications with an understanding that information will be shared. Protect your overall reputation, and don't sweat the minor slips that reveal, mostly, that you're not a paragon of perfection, maybe, but a group of human beings, struggling to make a difference under the usual conditions.
Last week, I shared my impressions of Google Wave, which takes current web 2.0/Internet staple technologies like email, messaging, document collaboration, widgets/gadgets and extranets and mashes them up into an open communications standard that, if it lives up to Google's aspirations, will supersede email. There is little doubt in my mind that this is how the web will evolve. We've gone from:
The Yahoo! Directory model - a bunch of static web sites that can be catalogued and explored like chapters in a book, to
The Google needle/haystack approach - the web as a repository of data that can be mined with a proper query, to
Web 2.0, a referral-based model that mixes human opinion and interaction into the navigation system.
For many of us, we no longer browse, and we search less than we used to, because the data that we're looking for is either coming to us through readers and portals where we subscribe to it, or it's being referred to us by our friends and co-workers on social networks. Much of what we refer to eachother is content that we have created. The web is as much an application as it is a library now.
Google Wave might well be "Web 3.0", the step that breaks down the location-based structure of web data and replaces it completely with a social structure. Data isn't stored as much as it is shared. You don't browse to sites; you share, enhance, append, create and communicate about web content in individual waves. Servers are sources, not destinations in the new paradigm.
Looking at Wave in light of Google's mission and strategy supports this idea. Google wants to catalog, and make accessible, all of the world's information. Wave has a data mining and reporting feature called "robots". Robots are database agents that lurk in a wave, monitoring all activity, and then pop in as warranted when certain terms or actions trigger their response. The example I saw was of a nurse reporting in the wave that they're going to give patient "John Doe" a peanut butter sandwich. The robot has access to Doe's medical record, is aware of a peanut allergy, and pops in with a warning. Powerful stuff! But the underlying data source for Joe's medical record was Google Health. For many, health information is too valuable and easily abused to be trusted to Google, Yahoo!, or any online provider. The Wave security module that I saw hid some data from Wave participants, but was based upon the time that the person joined the Wave, not ongoing record level permissions.
This doesn't invalidate the use of Wave, by any means -- a wave that is housed on the Doctor's office server, and restricted to Doctor, Nurse and patient could enable those benefits securely. But as the easily recognizable lines between cloud computing and private applications; email and online community; shared documents and public records continue to blur, we need to be careful, and make sure that the learning curve that accompanies these web evolutions is tended to. After all, the worst public/private mistakes on the internet have generally involved someone "replying to all" when they didn't mean to. If it's that easy to forget who you're talking to in an email, how are we going to consciously track what we're revealing to whom in a wave, particularly when that wave has automatons popping data into the conversation as well?
The Wave as internet evolution idea supports a favored notion: data wants to be free. Open data advocates (like myself) are looking for interfaces that enable that access, and Wave's combination of creation and communication, facilitated by simple, but powerful data mining agents, is a powerful frontend. If it truly winds up as easy as email, which is, after all, the application that enticed our grandparents to use the net, then it has culture-changing potential. It will need to bring the users along for that ride, though, and it will be interesting to see how that goes.
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A few more interesting Google Wave stories popped up while I was drafting this one. Mashable's Google Wave: 5 Ways It Could Change the Web gives some concrete examples to some of the ideas I floated last week; and, for those of you lucky enough to have access to Wave, here's a tutorial on how to build a robot.
Google is on a fishing expedition to see if we're willing to take web-surfing to a whole new level. My colleague Steve Backman introduced us to Google Wave a few months ago. I attended a developer's preview at Techsoup Headquarters last week, and I have some additional thoughts to share.
Google's introduction of Wave is nothing if not ambitious. As opposed to saying "We have a new web mashup tool" or "We've taken multimedia email to a new level", they're pitching Wave as nothing less than the successor to email. My question, after seeing the demo, is "Is that an outrageous claim, or a way too modest one?".
The early version of Google Wave I saw looked a lot like Gmail, with a folder list on the left and "wave" list next to it. Unlike Gmail, a third pane to the right included an area where you can compose waves, so Wave is three-columner to Gmail's two.
A wave is a collaborative document that can be updated by numerous people in real-time. This means that, if we're both working in the same wave, you can see what I'm typing, letter by letter, as I can see what you add. This makes Twitter seem like the new snail mail. It's a pretty powerful step for collaborative technology. But it's also quite a cultural change for those of us who appreciate computer-based communications for the incorporated spell-check and the ability to edit and finalize drafted messages before we send them.
Waves can include text, photos, film clips, forms, and any active content that could go into a Google Gadget. If you check out iGoogle, Google's personal portal page, you can see the wide assortment of gadgets that are available and imagine how you would use them -- or things like them -- in a collaborative document. News feeds, polls, games, utilities, and the list goes on.
You share waves with any other wave users that you choose to share with. User-level security is being written into the platform, so that you can share waves as read-only or only share certain content in waves with particular people.
Given these two tidbits, it occurred to me that each wave was far more like a little Extranet than an email message. This is why I think Google's being kind of coy when they call it an email killer - it's a Sharepoint killer. It's possibly a Drupal (or fill in your favorite CMS here) killer. It's certainly an evolution of Google Apps, with pretty much all of that functionality rolled into a model that, instead of saying "I have a document, spreadsheet or website to share" says "I want to share, and, once we're sharing, we can share websites, spreadsheets, documents and whatever". Put another way, Google Apps is an information management tool with some collaborative and communication features. Google Wave is a communications platform with a rich set of information management tools. It's Google Docs inverted.
So, Google Wave has the potential to be very disruptive technology, as long as people:
Adopt it;
Feel comfortable with it; and
Trust Google.
Next week, I'll spend a little time on the gotcha's - please add your thoughts and concerns in the comments.
The credit card industry is doing the right thing by consumers and enforcing proper security measures regarding the handling of credit card information. You might have heard about this - a number of the popular vendors of donor databases are recommending upgrades based on their compliance with these regulations. The "Payment Card Industry Data Security Standard", commonly known as PCIDSS, is a set of guidelines for securely handling credit card information. The standard has been around for about four years, but early enforcement efforts focused on companies with a high volume of credit card transactions. Now that they're all in compliance, they've set their sites on smaller businesses and nonprofits. So, what does this mean? Here's the simplest F.A.Q. that you're likely to find on the topic:
Do you ever process online, phoned in, or mailed-in credit card donations in-house? e.g., do you maintain the credit card number, expiration date and name of a donor?
If no, you don't have to worry about this.
If yes, do you have more than 20,000 such transactions annually?
Well, if you do, congratulations! Most nonprofits don't, so they qualify for level 4 of the PCI Compliance scale. That results in a Self Assessment Questionnaire (SAQ) Validation type of "4". Higher validation types are subject to stricter security standards.
The Self-Assessment Questionnaire will ask you all sorts of technical questions about your network and security procedures. Do you have a firewall? Are all of your transactions encrypted? Do you use anti-virus software? Is credit card information properly restricted to authorized staff?
Depending on your network, you might already comply with a lot of the requirements. If you don't, then it might require a significant investment to get there.
What will happen if I ignore this?
This isn't government regulation (although your state might have laws in place that do mandate some similar response). participation is mandatory. But, should your security be breached, two things will happen:
1. The compliance requirements for your organization will be reassessed to level one or two, and they'll be much more costly and complicated to meet. The credit card companies might decline to do business with you if you don't comply. Can you afford to not take Visa?
2. You will likely be indirectly fined for non-compliance. The credit card companies will hold your bank liable for losses due to credit card theft in situations where your security was substandard. Your bank will likely pass that fine on to you.
So what's the easiest way to deal with this?
Simple: don't handle credit cards. There are a number of services that, for a price, will do this for you, from Paypal and Google Checkout to CharityWeb and Blackbaud's BBNow. Outsourced ECRM software (NetCommunity, Convio, Democracy in Action, etc.) will also handle it. The cost is likely not as significant as that of maintaining compliance or suffering the consequences of a non-compliant breach.
I'll share that, at the Goodwill where I used to work, outsourcing wasn't an option, because we were both a charity and a retailer. Our frustration was not that we didn't have good security in place. It was that there were differences in how we had set up our security and the PCIDSS requirements. So, while we had done a lot of work and made significant investments, we still had to reconfigure things and spend more in order to be compliant. In addition to making our internal IT changes, we had to switch software programs in order to avoid storing credit cards unencrypted in our database, a typical problem. We also engaged a consultant. Once you are reasonably sure that you comply, then you must pay a security service to verify your efforts, another non-trivial expense.
Blackbaud has put together some good further reading on this topic (and they are one of the vendor's whose latest software is compliant; ask your eCRM vendor!).
Why don’t my report counts show the same numbers on your new system as they did on my old?
Ugh, do I ever hate to have this question come up in a project review meeting. It is surely my candidate for the question consultants least like to hear from a client.
And this question usually follows by a few weeks or months a close runner up question, Can you convert all my old data into the new system. Clients who ask this and consultants who answer yes are looking for trouble for themselves.
This has been on my mind as our team approaches the end of a current and some recent projects whose conclusion has been directly linked to resolving data ‘errors.’ Sometimes you find unexpected joy, such as last winter when a conversion from a really old Raisers Edge version to Giftworks provided historical donation totals that matched entirely. Not to be a pessimist, but yup, I was surprised.
In our hearts if not our experience, we all know that data conversion gaps occur way more often. Here are some thoughts for “both sides” to keep in mind in approaching that next software upgrade.
First, as a background philosophical thought, if an organization’s data looked just right in its old system, would you still need to upgrade or replace? Business practices change and the old ways no longer work. We generally welcome change and we can expect staff to look forward to operating in new forward-looking ways. Yet fitting the old data to the new may be, as a colleague said yesterday may be mixing apples and oranges. The old and the new may never align again.
If you do convert piles of old transaction data or program enrollment data, and the new system has involved strategic planning and incorporation of new business rules, accept that reports will look different. Embrace the new and appreciate it.
Second, conversely on the human or philosophical side of things, you have to make an estimate of how much staff not just “hate the old way” but really are ready to “embrace the new way.” I think of a data conversion some years ago where staff continued to run mailing lists from their old system months after they were doing data entry in their spiffy new system, with its way cooler list generator. Hostage syndrome. They had grown hostage to the features that bore down on them in the old system. So if things ARE going to look different, you need to prepare everyone for it 100% or life will be difficult.
Part of the way to do this is to make sure staff at all levels of the organization are in the room when you discuss data migration. It is not sufficient to just look at reports and lists and to talk with the managers who use them. Let everyone hear how admin and program staff actually enter data, the compromises they make, the guerrilla warfare they may be waging against existing data validations to put what they want where they want it. This may be sobering to senior management and support realism about the conversion.
Third, consider if you can just leave historical data where it is. If you have been paying for a proprietary on-line data system that you want to stop paying for, you may have no choice but to extract old data and put it somewhere it can still be used. If not, why not just continue keep the old system available to run historical reports and start fresh with the new? Two pending conversions to Salesforce to replace a collection of spreadsheets and old Access databases have been way pleasant from a decision to not incorporate years of messy and unaligned old data.
Deciding not to convert may be a major policy decision if senior management or the board is used to a certain kind of review. I don’t underestimate it. But it is worth pursuing the question at the outset, before anything starts.
Fourth, consider converting just top level data, such as all primary demographic and status information for current contacts and leaving aside in the old system. Start with just what you know to be clean and essential.
Fifth, a variation on the third, fill in complex and messy old data by hand over time. As new cases or activity occurs for a contact, fill in or correct the gaps in their data from the old system. Meanwhile, don’t try to run multi-year historical reports on the new system
Sixth, if the data is messy, clean it up parallel to and prior to switching to the new system. My experience: most of the time, it is going to be easier to correct messy data either in its present home or in some convenient way station. In another conversion to Salesforce, where the data now resides in Filemaker, we have agreed to freeze data entry for a bit, and pull the data into a combination of Excel or Access where it will be more susceptible to bulk manipulation and checking.
Seventh, tell the consultant everything you can. If you are relatively new and the system is not well documented, find the staff members who have been there long enough to explain quirky things lost in the mists. In a current conversion from a proprietary undocumented membership system to CiviCRM, we have had one gotcha after another. For example, the current system shows five membership levels. The new system will have the same five membership levels. The paper forms show five membership levels. We checked at the beginning. Great! Easy! Except a faction of the members, in their actual extracted data showed a sixth membership level. And CiviCRM importer chokes on those records so it has to be addressed. OK, we figured this out, but if you add up field by field the consultant detective work to resolve things like this, you suddenly have blown a reasonable data migration budget.
Eighth, agree to leave data conversion out of proposal bids and do it on a time and materials basis only. This will enable everyone as the inevitable problems arise to make pragmatic decisions. Yes, it is worth it to write a script to fix this problem. No, it is not worth it, leave it alone. Or, yes, we need this and organizational staff will fix it ourselves or hire temps to do it.
I regularly resolve not to submit proposals where I have to include data conversion in the cost estimate, and I regularly find myself unable to keep that commitment. Even if you allot a few hours as part of a preproject assessment, it is unlikely you will find all the problems. A current project that is not exactly a system migration, but instead will need to enable staff to use purchased business data in a Drupal-based research and organizing framework. The data is good, used nationally and expensive! It should be clean say the developers! Yet even here we find quirky things. What should we make of a crucial research field which sometimes is stored as an actual dollar amount and sometimes as a coded list of dollar values. Since this is an ongoing data feed and not a one-time data conversion, we need to address it so that data searches will work on both kinds of cost valuation figures. And it’s just not realistic to expect to find all this stuff before you get pretty deeply into it.
Nine, if you are the consultant, you often, not always, do a trial conversion, leave it on a development site for a while for testing, and then do the final conversion to go live. It is really important to carefully document the conversion steps. In one really messy conversion, we ran, tested and refined the 40 or so separate conversion scripts several times before deciding the soup was ready. Different people contributed to the scripts. Having the scripts catalogued and organized lessened the pain of having to rerun them. Plus even a year later, it was possible to go back and find the script that massaged this messed up status category or performed some other task when the client asked about “what happened to the people with interest code x”?
Ten, hmm. I am leaving a slot for you, veterans of data conversions. Your thoughts? I could certainly use them…
Meanwhile, this post derived from a suggestion from fearless editor Laura Q to write about the question consultants least like to hear from clients. When I posed this to my co-workers here at Database Designs, I got so many suggestions, I first thought of doing a “top ten” and decided to just start with my “favorite.” This could turn into an occasional series, and to balance, my colleague Mimi suggested one on questions consultants MOST like to hear from clients.
I recently wrote about the potential for shared outcome reporting among nonprofits and the formidable challenges to getting there. This topic hits a chord for those of us who believe strongly that proper collection, sharing and analysis of the data that represents our work can significantly improve our performance and impact.
Shared outcome reporting allows an organization to both benchmark their effectiveness with peers, and learn from each others' successful and failed strategies. If your most effective method of analyzing effectiveness is year to year comparisons, you're only measuring a portion of the elephant. You don't practice your work in a vacuum; why analyze it in one?
But, as I wrote, for many, the investment in sharing outcomes is a hard sell. Getting there requires committing scarce time, labor and resources to the development of the metrics, collection of data, and input; trust and competence in the technology; and partnering with our peers, who, in many cases, are also our competitors. And, in conditions where just keeping up with the established outcome reporting required for grant compliance is one of our greater challenges, envisioning diving into broader data collection, management and integration projects looks very hard to justify.
So let's take a broader look this time at the justifications, rather than the challenges.
Success Measures is a social enterprise in DC that provides tools and consulting to organizations that want to evaluate their programs and services and use the resulting data. From their website:
Success Measures®, a social enterprise at NeighborWorks® America is an innovative participatory outcome evaluation approach that engages community stakeholders in the evaluation process and equips them with the tools they need to document outcomes, measure impact and inform change.
To accomplish this, in 2000, they set up an online repository of surveying and evaluation tools that can be customized by the participant to meet their needs. After determining what it is that they want to measure, participants work with their constituencies to gather baseline data. Acting on that data, they can refine their programs and address needs, then, a year or two later, use the same set of tools to re-survey and learn from the comparative data. Success Measures supplements the tools collection with training, coaching, and consulting to insure that their participants are fully capable of benefiting from their services. And, with permission, they provide cross-client metrics; the shared outcomes reporting that we're talking about.
The tools work on sets of indicators, and they provide pre-defined sets of indicators as well as allowing for custom items. The existing sets cover common areas: Affordable housing; community building; economic development; race, class and community. Sets currently under development include green building/sustainable communities; community stabilization; measuring outcomes of asset programs; and measuring value of intermediary services.
Note that this resources nonprofits on both sides of the equation -- they not only provide the shared metrics and accompanying insight into effective strategies for organizations that do what you do; they also provide the tools. This addresses one of the primary challenges, which is that most nonprofits don't have the skills and staff required simply to create the surveying tools.
Once I understood what Success Measures was offering, my big question was, "how did you get any clients?" They had good answers. They actually engage more with the funders than the nonprofits, selling the foundations on the value of the data, and then sending them to their grantees with the recommendation. This does two important things:
First, it provides a clear incentive to the nonprofits. The funders aren't just saying "prove that you're effective"; they're saying "here's a way that you can quantify your success. The funding will follow.
Second, it provides a standardized reporting structure -- with pre-developed tools and support -- to the nonprofits. In my experience, having worked for an organization with multiple city, state and federal grants and funded programs, keeping up with the diverse requirements of each funding agency was an administrative nightmare.
So, if the value of comparative, cross-sector metrics isn't reason enough to justify it, maybe the value of pre-built data collection tools is. Or, maybe the value of standardized reporting for multiple funding sources has a clear cost benefit attached. Or, maybe you'd appreciate a relationship with your funders that truly rewards you with grants based on your effectiveness. Success Measures has a model for all of the above.
Even if you will never tweet, it's obvious that Twitter is a source of useful information, and, in some cases, a more timely source than traditional search engines and media. If you use Firefox as your main web browser, and have the popular Greasemonkey add-on installed, which serves as a kind of macro language for the web, then the Twitter Google Results script adds some real power. Any Google search you perform will also search Twitter, posting the top five relevant results. Why is this useful? Well, when we heard rumors that a bomb had gone off somewhere near our Bozeman, Montana office, the Twitter results had current info and links that weren't indexed by Google yet
Namechk checks for your preferred username on a slew of Web 2.0 sites, from Bebo to Youtube. I found this useful to reserve peterscampbell at a few sites that I want to use but hadn't signed up for, and to learn that some other guy named peterscampbell had already grabbed it at Youtube, where I had used a different loginname... snap!
This is a tip, not a tool - if you've been stymied by Facebook's recent changes to how it handles updates, you can make a lot more sense of it by making lists of related friends, and then filtering the updates by group. Click on Friends and the "Create New List" button is at the top of the screen. I have lists for family, nptech, Boston friends, SF Friends, and a special one called "no tweets", which filters out everyone who cross-posts all of their Twitter updates to Facebook (my default view). Keeping up with all of this info is always a challenge, so the ability to filter out the echoes is a must.
Exhibit is a web site that lets you upload spreadsheets, maps and other data to an information rich, filterable, active web page that can then be shared. If your org works with a particular environmental cause, seeks a cure for a disease, or supports a particular community, you can share data about your cause dynamically and expressively with this amazing site.
Google revolutionized email with GMail, the first email platform in decades to question the basic assumptions about how email should work (by filing important email into folders). They're about to do the same thing with Voicemail. A year or two ago, they purchased Grandcentral, a service that allowed you to route multiple phone numbers to one shared voicemail box. A few months ago, they opened the revamped Google Voice to existing Grandcentral customers, and, surprise, it looks a bit like GMail.
When I look at GMail, Google Voice, and the recently announced Google Wave, a real-time communication and collaboration platform, and then picture these all integrated into a Google Apps account, it becomes clear that our phone systems are moving into the cloud as fast as our servers are, and, while it is always that controversial proposition of Google giving you stuff in return for the right to market to you based on all of your data, it still looks like they are poised to offer one of the most powerful, integrated communication platforms that the world has ever seen.
Have you run into any awesome things lately worth sharing? Leave a comment!
Let's get a bit geeky. Many Idealware visitors come here for advice on purchasing and deploying data management systems, such as donor databases, constituent relation management systems and content management systems. And, more often than not, are replacing older systems with new ones, meaning that one of the trickiest tasks is data migration. If any of this work has ever fallen to you, then you might have found yourself doing tedious editing and corrections in Excel, pouring over data screens or rows in Access trying to formalize non-formalized data entry, and generally settling for some lost or incorrect data moving from old system to new.
Wouldn't it be great to have a magic wand that can instantly reformat the data to the proper format? Well, I have one for you. But, just as Harry Potter had to go to school before he could effectively wave his wand, mine comes with a lesson or two as well.
The wand in question is a search/replace language called regular expressions. Regular expressions are a set of terms that can be used, in supported software, to perform advanced search and replace functions. They were originally popularized in the Unix Stream Editor (SED), but are now standardly found in text editors, word processors, scripting languages (such as PHP) and other software, usually as an advanced option.
The reason to use them instead of a regular search and replace function is simple: they can search for things that regular search tools can't. For example:
the first three characters at the beginning of each line
the three at the end of each line
one or more spaces
Regular expressions can also do multiple replacements in one phrase, allowing you to either remove the first comma encountered in a sentence, or all commas. Here are the basics:
A regular expression takes the form of /Search Phrase/Replacement/. A simple search to replace all instances of the word "fish" with the word "bird" would look like:
/fish/bird/
But regular expressions only prove their worth when you learn their special characters:
. (any character)
* (one or more characters)
^ (the beginning of a line
$ (the end of a line)
() (parentheses surrounding characters in the search phrase can be recalled in the replacement)
$1, $2 (substitute in the replacement for characters saved by parentheses in the search phrase)
\ (backslashes treat the next character literally, even if it's a Regular expression special character)
[a-z], [0-9], [A-Za-z] (groupings search for all of the characters specified between the brackets, using dashes to identify ranges
Examples:
If you have a text printout of a document that you want to whittle into something more useful, like a CSV file, step one might be to remove any dead space.
/ */ /
will search for one or more spaces (the asterisk means "any number of the preceding character) and replace them with one space.
/^$/d
will remove all blank lines (lines with nothing between the beginning and the end of the line)
If you are moving data from one system to another, you might have to reformat dates for the new system. Say the old system exports dates as MM/DD/YYYY and the SQL database you're importing them to expects YYYY-MM-DD. This Regular Expression will convert all dates to the new format:
( - parentheses surround things that we want to remember, so this starts a section we'll remember.
[01][0-9] - a month (MM) will be a number between 1 and 12, so, if your system is exporting dates with leading zeros (if not, you can do this with a series of regular expressions to get around that), then the [01] set will match either a leading zero or a one. The [0-9] set will match any digit following that one or zero.
) - this will be remembered in the replacement as $1, because it's the first thing we remembered.
\/ - since the slash is a regular expression special character (the delimiter), we precede it with a backslash, telling the parser to treat it a a slash, not a delimiter.
([0-3][0-9]) - this will find any pair of numbers between 01 and 39, which we know as the day, and remember it as $2, because it's enclosed in parentheses.
\/ - next slash
([12][0-9][0-9][0-9]) - this catches the year. You see how, right? It is specifying that the year will be in this millennia or the last by limiting the first character to one or two. We use parentheses to remember this as well.
/ - this slash signifies that the search phrase is done, and the replacement will follow.
$3-$1-$2 - this takes our three remembered phrases and reorders them from month, day, year to year ($3), month ($1), day ($2), placing dashes in-between them.
/ - finally, we close the command with a slash.
One of my standard uses is to take a list - which could be an Excel spreadsheet, or a database dump, or a Word table -- clean it up, and then format it into SQL statements that can then be pulled into a database. Most databases can import in CSV files, but Excel, while good at doing some reformatting, can't do the fancy cleanup tasks that my regular expression-enabled editor can. Once my specific clean-up chores are done, if I'm left with a tab-delimited file, I can do the following three simple searches to turn it into a SQL input file that can just be run in my SQL interpreter.
/\t/','/ -- searches for all tabs (\t is a symbol that means "tab") and replaces them with ','
/(.)$/$1');/ - searches for the last character in a line and replaces it with that character followed by a close quote, close parens and semi-colon.
/^(.)/insert into players (name, title, company) values ('$1/ - searches for the first character in any line and prepends the front end of the SQL statement.
If we had an input file with lines like this:
Joe Namath Quarterback Forty-niners
It would become
insert into players (name, title, company) values ('Joe Namath','Quarterback','Forty-niners');
There are plenty of excellent resources for learning about regular expressions on the web, but many of them are targeted at programmers, making them a bit thick to read through. For more friendly introductions, I recommend The regular-expressions.info quickstart. While many text-processing tools, including Microsoft Word, support regular expression search and replace, I recommend using a good text editor over a word processor, because it will likely include supporting functionality, such as block copying/pasting, and they'll handle very large files with far more speed and grace. I've been happy using TextPad and EditPlus on Windows, and TextMate and TextWrangler on the Mac. Wikipedia publishes an incomplete list of applications that include regular expression functionality.
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