As deficits increase, unemployment continues, and tax revenues decline, government has to shrink. An important question is, will government “shrink smart”? Or will the axe fall randomly or primarily on the weak and unconnected?
I’ve always been involved in a research, development, consulting, or management capacity with systems that distribute, share, or improve access to information. As a result, my understanding of the meaning of collaboration has evolved into “people working together and sharing information to achieve a common objective.”
Over the past 5 years my focus has included the use of social media and social networking in support of collaboration. That’s not just because I think “it’s nice to share” but because I think collaborating and sharing information make economic sense and promote innovation.
At the same time I’ve realized that not everyone is ready to “buy into” more modern and collaborative technologies such as those that make it easier to share both work and personal information more openly with a team or work group. Sometimes resistance occurs because old habits are hard to change. Sometimes it occurs out of a concern about privacy or national security.
However we may feel about making decisionmaking and collaboration more open and “transparent” to public scrutiny, the focus of government when funds are shrinking must be on making smart decisions about public services. To me this means either reducing the services in a fair and equitable fashion, or working collaboratively to make the most of the resources that we still have.
Here’s what I think should happen when someone in a government office or agency has a problem that needs solving:
- Find out who knows the solution — no matter where that person is located.
- Contact that person.
- Get help from that person.
Yes, I understand very well all the practical, organizational, and political challenges to this happening. And, yes, there will always be someone on the team who insists on sending out multiple emails with attachments instead of directing team members to a shared resource, thereby doubling the effort needed to gather and collaborate on development of a common document.
But if (1), (2), and (3) above can occur quickly and efficiently, shouldn’t the total cost to the public of the problem’s solution be less than it would have been had it been necessary to start completely from scratch?
What you see emerging here is a classic definition of “knowledge management” which in the past focused on capturing the artifacts that contained recorded media. The situation we find now is that modern networking technologies can incorporate information about interests and skills and allow people to build and maintain relationships that bypass traditional organizational and professional boundaries. The result is — in theory at least — that by your knowing in advance something about a lot of people, the likelihood of finding a relevant solution increases.
This is similar to how jobseekers have always been encouraged to begin professional networking before they need to look for a new job. Here the idea is that people should be encouraged to build professional knowledge-sharing relationships in advance in order to maximize the likelihood they can contact the right person when the need arises. While technology can certainly help — look at the flow of information through public systems like Twitter and Facebook and various behind-the-firewall solutions available to large and small organizations — understanding the potential value isn’t rocket science.
Does this necessarily mean that promoting social networking among professionals, irrespective of organizational, professional, or geographic boundaries, will automatically reduce the cost of finding solutions to problems?
Obviously there’s more to it than that. Systems, projects, and work groups don’t manage themselves. Problems don’t always get “solved on their own” even if “crowdsourcing” is used. There’s still a need for leadership and initiative.
And there is definitely a role for technology to aid in this type of “intelligent networking” given the large number of people who are in a position to contribute in large collaborative networks. There’s also a time and place for highly structured outreach programs such as the CDC’s H1N1 outreach program and the GSA’s current ExpertNet initiative.
The question is, though, what are the cost and timing implications of making collaboration tools more accessible and usable to large numbers of people in different organizations? It’s not automatically true that involving more people in problem solving will necessarily reduce the time and cost of solving a problem; Brooks’s law and the mythical man-month would seem to argue otherwise, at least in the context of software development. Plus, if you’ve ever read through the comments left on a discussion blog by the public you’ll see some real differences in dedication and interest — as well as downright trolling. “Opening things up” doesn’t automatically lead to fresh and clever solutions bubbling up to the surface.
What makes more sense to me when developing the metrics to track the costs and benefits of collaboration is to consider at least two types of collaboration:
- Type 1 collaboration is project- or task-specific and involves collaborators in performing a specific task or accomplishing a specific goal. The linkage between the costs and resources associated with collaborative behaviors (e.g., sharing information, making decisions together, meeting to review and discuss issues, etc.) and the defined task or goal supported by collaboration is relatively clear and can be documented. Here traditional concepts of efficiency can be introduced as the basis for metrics that track the relationship between collaboration and supported work.
- Type 2 collaboration is more background oriented and involves people working together normally on a day to day basis and sharing information and knowledge in a more social manner. The classic example is “gossip around the water cooler.” The linkages between costs and resources devoted to “networking,” and the eventual ability the organization has to take advantage of these relationships and the information and solutions that can traverse them, are more difficult to articulate.
But not impossible. My hypothesis: people who are more collaborative and who know more about what other people know are more effective at getting things done. They should be in a better position to decide when someone else can help them solve a problem and when they need to solve the problem on their own. Our current infrastructure of knowledge management and search and retrieval systems are based on this premise.
One of the characteristics of a good manager is knowing when — and to whom — to delegate responsibility. Another characteristic of a good manager should be to know when to go it alone and when to reach out to tap the expertise of others.
Putting networks and systems in place to help ensure that happens is obviously a key element in making sure effective collaboration takes place. But it will still be up to management to encourage — and reward — such behavior.
Copyright (c) 2010 by Dennis D. McDonald. Email Dennis at email@example.com.