Innovation can involve small adjustments or great transformations. Social media provides a case study for understanding why ongoing monitoring and evaluation can tell many different stories about whether change is big or small, for good or for not — or something altogether different.
Online social networks like Twitter and Facebook often notify their users of certain use milestones like ‘friend anniversaries’ or acknowledging the number of posts or the date of joining. These often serve a reminder of not only length of use, but patterns of use. Both provide useful insights that can illustrate the need to incorporate monitoring and evaluation in any innovation effort.
I recently had a ‘friendversary’ on Facebook with someone I’ve known for 30 years and looking back on the photos that the site offered chronicling our friendship (as recorded on the site) I was struck how much my relationship has changed with the social network and how little has changed with my good friend.
It’s easy to forget how transformative social media — or Web 2.0 (remember that?) — was when it first emerged. The idea of a participatory web where people could create, remix, and distribute multimedia information rapidly, cheaply, and with little understanding of computer programming was revolutionary. Platforms like Facebook, LinkedIn, and Twitter (and their early social network kin like Friendster, MySpace, Classmates.com, and Second Life) changed the way we communicated with each other, organized, and learned.
Remember when you first got email and opened up your client to find, with some excitement, that “ooh, I’ve got mail!”. Now, people are drowning in email, with estimates that people are spending more than 1/4 of their working time simply dealing with email. Then there’s the work-related messages on myriad tools like Slack, WhatsApp, as well as those on LinkedIn, Twitter, and Facebook. While some suggest this social economy can generate new productivity, many of us long for the days when these tools provided real value.
Those times when we wanted to share things on Facebook, when Twitter allowed you to connect to people you’d never have met otherwise, or when we found much signal and little noise in our inboxes or even our scientific journals and our science, now are immortalized in these anniversary notifications.
The answer, as illustrated in a previous post, is: our systems.
These innovations, due partly to their ease of adoption, rapid uptake, and broad reach, have changed not only the function of our work, but the entire economy of our worklife. If one was to ask me what the value of Twitter was to learning and connecting ten years ago, I would have said it was invaluable. Now? It’s value is a fraction of what it was. Facebook is something I’ve never really liked, but now only use sparingly because its the only way I have to communicate with some people I care about who feel they are locked in to the dominant design of platform and won’t change…yet.
This illustrates the fundamental issue around innovation value and its effects and why understanding both requires monitoring and evaluation plans that account for change over time. Is social media good? The answer always depended on a number of things (for whom? when? under what circumstances?), however those answers are quite different now vs before.
Furthermore, the answers themselves have different meaning. The early days of social media metrics involved things like followers, ‘likes’, and shares. For example, someone with 2000 followers was considered to have half the potential reach as someone with 4000 followers. The numbers, which were always problematic, at least provided an approximate sense of influence and could generate questions about impact.
What made this data somewhat reliable were two things: 1) the authenticity and originality of the content produced and 2) the integrity of the connections and interactions made through social networks. To illustrate, there was once a time when there were certain aesthetic features that were rare and thus, sought after on Instagram. Soon, the ease of use, speed of transfer, and reach of social media allowed ideas to replicate fast so that these once rare features were widely copied. Now, because of scale, the amount of replication is enormous and original or authentic perspectives are harder to find. The value of the platform has now changed.
The other issue is the rise of AI and human-assisted marketing and related frauds. Instagram tried to crackdown on these fraudulent accounts, however the industry behind these fake accounts who offer to sell people followers suggests this is going to be a long battle. Facebook (Instagram’s parent) is facing the same thing, particularly with election issues. Content is much less authentic and novel and the trustworthiness of the feedback and even the original posts themselves is now suspect. Yet, people continue to post and share and engage.
Social media is a very public, pervasive example of an innovation that was developed with some original purposes in mind, changed and evolved its service model over time, and transformed the environment it operates while doing it. Not all innovations have such obvious, wide-reaching implications, but most still require some understanding of what is happening now and what happens tomorrow.
This understanding comes from capturing a baseline of what is happening now. This includes metrics and assessments of both the innovation itself and the ecosystem in which the innovation exists. The Living History method is one way to capture this start point and what comes from it. A baseline is necessary because change is always in relation to something at a certain point of time.
A qualitative assessment of the innovation is also needed. As the cover picture above illustrates, a butterfly exists in multiple states that are vastly different from one another. To the extent that each state represents a ‘true’ butterfly is open for debate, but the differences related to time, physical composition, function, and capability is enormous and each contribute to a particular stage of life and role in the environment.
Evaluation for transformation means capturing data at the appropriate timescale. For a butterfly, this might mean monitoring its conditions over the course of days and hours. For understanding ocean change, this might be over decades. For a service program, the answer might be over months. The key is starting up a monitoring program that involves paying attention to what is happening in and around the innovation and capturing the kind of data that tells that story.
Without putting in place a means to tell the story and monitor what happens, there is a risk of mis-attributing certain causes and effects and missing key developmental signs that your innovation is going from helping things to making things worse very quickly. The story of social media is still being told, but the example of it (and email and other productivity tools) follow a pattern that Marshall McLuhan saw coming that we have the ability to influence, if we pay attention. If we do, we might be able to avoid creating the very horrors of innovation that designer Charles Eames wrote about.