It’s everywhere! People are talking about it in all aspects of life. Business, research, education, economics, socialnomics… you can’t escape it!
Data is everywhere and in everything that we do. If you’ve bought anything, searched for anything or signed up for anything online you’re part of big data.
Our schools gather data all the time on students, parents, faculty, the assignments given, the tests taken, all of it contributes to data used to measure schools and those inside their walls.
Dashboards, info-graphics, charts, spreadsheets and reports are issued using all of the data at our disposal to paint the clearest picture of how “things” are going. But how do we know that the data is right and those “things” are being reported on correctly?
Data is fraught with errors, omissions, and mis-entered information. It’s because of this that we need to focus on Little Data.
Mark Bonchek (@MarkBonchek) in the Harvard Business Review defines Little Data as:
“…what we know about ourselves. What we buy. Who we know. Where we go. How we spend our time…”
But what I am talking about is smaller than that, what I am talking about it how we manage the discrete pieces of data that we capture and enter before we can make use of any of this information, spot trends or make predictions.
Why do we need to focus on Little Data you might ask? Because we are only as good as our data.
On January 20th, 2014 Fox News Insider reported on a family that received a disturbing piece of mail with information about their daughter’s recent death in a car crash in the address field. The company in question blamed “computer error,” but an executive admitted that human error along the way was to blame.
When you see things like this in the news you may think to yourself how could that happen? What carelessness! But as we think about the systems that we manage in our schools and organizations we might be recording this same type of information in our development or admissions systems and how do we know we are doing it right?
A plan on how we manage this Little Data needs to be developed and agreed upon by you school or organization first before Big Data can be trusted and used. Following a set of rules and guidelines can help avoid errors and embarrassment.
I have been writing about and consulting on data management for quite some time now and in that time I have had a number of thoughts and ideas which I have developed into a guide for my school and others. It focuses on:
- Data Domains: Those offices and areas in you school or organization that either have their own data system(s), needs and requirements. Developing a chart of these various domains, along with their various data systems, points of entry and support systems is paramount to gains a complete overview.
- Data Ownership: There are multiple pieces of data within any school or organization and there needs to be clarity as to what domain is responsible for those pieces. This can become more complicated when it comes to biographical and demographic data that is shared across these domains. A person can be a parent, an alum and employee of a school and what domain is responsible for an address change when required? Admissions? Development? Human Resources?
- Data Events and Flow Chart: Any school or organization should take time to identify those event that occur within and detail the impact of those events and the domains effected. Any information which needs to be communicated or shared with other domains can then be done either electronically through data syncing, export/import, email or via other analog means.
- Data Rules and Style Guide: Once we know what the domains are, who owns the data and how it flows within we can focus on the rules for entry. As they say “the devil is in the details” and this is where we define those details. Prefixes and suffixes, address information, relationships, marital status, grades and employment data are just a few of the items that should be covered. The guide should be a shared document, that each domain feels that they have contributed to and owns. It should cover not only the way in which data is enter, but the ways in which is should not be entered. Things like one piece of data per field (don’t enter two email addresses in a field designed for one) and putting the right piece of data in the right field (don’t use a field designate one piece of data for another that you can’t find a spot for).
- Data Examples: Providing examples of where data failures can and in some cases have occurred is helpful. You want to be sure to illustrate where the breakdown(s) occurred as well as the steps that can be taken to recover.
Even with all of these things covered, there can still be issues that will impede your ability to get Small Data right. System design, data sharing, communications and data formatting can all pose problems, but these are hurdles that can be overcome.
If systems aren’t inherently interconnected you should look for the least common denominator(s) for sharing data. Is there an available API for connecting systems? Do the systems share a similar backend (SQL) or have some sort of shared “connector” (OBDC)? Can you export data as either a CSV or tab-separated values? Can you move to a better system, one that has a shared backend or customer (constituent) relationship management (CRM) system?
Big Data can give you what you want and help you make important decisions about your school or organization, but in order to get the most our of that data you need to make sure your Small Data is right first. Take time to talk to the people in the various domains to see what their issues and needs are. Involve them in the process. Conduct a school/organization wide audit of you data and systems to make sure you aren’t missing anything. Once you have all you information gather take time to construct a set of rules and guidelines that make sense your school/organization and it’s data needs.
You can download a copy of the guide I developed here: Data Rules & Standards.
[Shared under Creative Commons Attribution-NonCommercial License]
Well done and all good points. I especially value the idea of putting together a flow chart. I’m often surprised to hear that even some database owners are unaware of the number of systems that need to be updated, let alone that it must be done by a human. With this misunderstanding there will inevitably be a loss of communication and bad data residing in the others. When refresh time comes around, that bad data may even be recycled back to that recipient’s database.
A flow chart can also help a group visualize the information and better understand where the breakdowns are from both a technical and communications standpoint.
Nice piece William! I’ve been on the “small data” crusade for a couple years now (and actually worked with Mark at McKinsey interestingly enough) and totally agree that “you need to make sure your small data is right first.” If you / your readers are interested I’ve been writing about the topic at http://www.smalldatagroup.com – where I actually have my own definition for small data that fits somewhere between what folks think of with big data and Mark’s view of little data. Good stuff!
Allen
I love this and your definition…
“Small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.”
I think it’s particularly applicable in the education setting for which I work. You site looks like a fun read. I look forward to poking around.