Numbers Don’t Lie
I had been working with a rural community in the Dominican Republic for several months on a housing program. The project relied on strong community involvement and it was frustrating. They were not moving as fast as I thought they could. I was anticipating significant cost overruns.
Still, as I finished my pencil and paper tally (yes, this was before Excel), I was not prepared for such a big a cost overrun.
I walked into the next meeting, armed with the numbers, my interpretation of their failure, and some righteous indignation. The community members were shocked by the information too, but they accepted it, acknowledged their failure, and agreed to the consequences. It was a rough meeting.
But not as rough as the next one.
Two weeks later, I noticed my error. A simple math mistake. The kind that Excel might have protected me from. In fact, the project had come in under budget. So at the next meeting, I came with new numbers, a tearful apology, and a big dose of humility.
There are two easy lessons in here, and one very hard lesson. I want to focus on the hard one, so let’s dispatch with the easy ones first.
Getting the numbers right. Of course, when presenting data we need to be accurate.
Watching out for confirmation bias. If I had not expected to find a cost-overrun, I might have triple-checked my math when the data surprised me.
Here is the hard lesson, the one that stings.
There is a dangerous intersection between power and data. The lesson lies in the way I — the white, North American, development worker who is in charge of the money — took some numbers and used them to tell a whole community who they were and what their story was. The lesson lies in the way those community members accepted my “right" to tell their story in my way. My right to hold all the information in my hands, to unilaterally decide its meaning, and to impose the consequences.
I may not have even seen this lesson had I not made such a mistake.
Many of us work in positions that require us to bring data to others – to a community, an organization, a team, or a client. In this work, we are frequently standing at that dangerous intersection between power and data. Sometimes it is hierarchy, education level, race, but in every situation, access to information – in and of itself – creates an imbalance of power.
Here are a few insights from a learning-centered perspective, to navigate this intersection.
- Collectively fill in the story. They say that numbers don’t lie. Maybe not. But they also don’t tell the whole story. They are devoid of context. They are devoid of emotion. They are open for interpretation. A fuller story emerges when we put the data into people hands. When groups collectively explore, question, fill in the gaps, and extract insights, we share power. We co-create the story and co-own the actions that might follow.
- Be compassionate and authentic. Compassion does not mean sugar-coating. Rather, it means avoiding judgment and acknowledging the range of human emotions that the data might inspire. Authenticity is not the same as objectivity. Authenticity is the open and honest expression of any viewpoint that may have shaped your choices of data, and freely acknowledging what is known, and what can only be surmised.
- Use data as a witness, not as a prosecutor or jury. Insights emerge when people approach the data with courage and curiosity. For that to happen, we present the clearest picture we can of what we see and recognize that others may see something different. This is tricky if the data is bad news, but we make it easier for people when we withhold our pronouncements of guilt or innocence.
Question: What are some ways you have found to navigate this dangerous intersection?