Metrics/Evaluation 2.0, Part Two
Posted On: August 26, 2019
An update from FMC Senior Advisor Darlene Wolnik on the ongoing development of its Metrics product and on FMC’s work in providing overall evaluation and technical assistance to markets and networks.
Part Two: Market Needs
To illustrate the spectrum of different market needs in terms of evaluation, here is an outline of some market organizational perspectives in one state that is working with Metrics:
Group A: Market orgs already collecting and using data regularly. That group is often teaching their network and FMC what reporting functions to add through their creative use of the data. We do find that they appreciate the added citations and data we add to Metrics reports (i.e. how much farmland is being lost in the US underscoring their own data of acreage saved by their vendors use) and that they use both the Summary Report and widgets easily. What they don’t like is being told what metrics to collect or even how to use their data. We also see that their collection methods can usually use a serious upgrade, meaning data isn’t always collected in the same manner every time or that they ensure that enough data is collected before they do analysis or reports. And they usually collect a LOT of data, much of which they don’t use. Many in this cluster also want a level of functionality that works with online vendor database systems. To that end, we began a partnership with Farmspread a few years back using it to manage vendor invoicing and business details while relevant data immediately fed into Metrics.
How to help?
Networks can help these markets to find a data partner, such as a university researcher or an economics professor, and by providing some needed structure and facilitation between the market and the data partner.
This cluster of markets can be also supported by having them present to other markets and to write up their experiences. Networks also find it helpful to ask some to be advisors to the network, maybe even asking one or two to seek out and share relevant published research on farmers markets as a way to stay abreast of the trends. Without a doubt, these entities are willing to engage in professional development opportunities which can be centered around training better data collection and how other food system entities are using data, and asked to then share that new information with their peer markets.We sought the right partner on the vendor data, and found the Farmspread platform which is well-designed and had the same goals that we did and was customer-focused. The partnership has also allowed us to have a technology partner willing to invest in the farmers market field.
Group B: Market orgs that are collecting data chiefly because the network has asked them to collect it and because the network can use it. Often networks think that markets not willing to use data for their own purposes is a bad thing, but it doesn’t have to be seen in a negative manner. The good news is that these entities believe in the power of the network and is willing to use some of its time to build that network. And they will usually collect the data in the manner that the network prescribes. Still, these entities are usually reticent about doing any policy work or even releasing market level data to their own community.
How to help?
One way for networks to help this cluster is by modeling best practices: sharing strategies like the network’s use of data on social media, tagging those markets and even directly sharing how they follow up with media and stakeholder contacts relevant to that market. We find this cluster is often on the cusp of being data users, once they see how effective it can be via their network(s), especially when they start by choosing data points that they can collect easily and use immediately. They usually prefer the individual widgets over than the Summary Report. This cluster may greatly benefit from using resources such as FMC’s audience worksheet, which helps refine the choice of Metrics and define the likely users of the ensuing data. The network can also help by building sister market relationships with an entity from Cluster 1 or finding one through the Metrics group list. The network can also seek out local partners for data use, such as the businesses in the nearby Main Street.
Group C: Market orgs that are mostly using data to do internal analysis. Those orgs usually don’t want to collect sales data (which every network has as its data goal) or even to release much data. They take data seriously but use it via on-the-spot analysis, eschewing complicated systems. Often this group understands the reason for disciplined collection methods, often having been trained by researchers or professors. They like the dashboards or spreadsheets of data that are embedded into Metrics more than the reports.
How to help?
They appreciate help with analysis that is aligned with other retail data, such as sales per shopper or vendor category analysis or the same data point being compared over time, such as season-to-season. Networks can also support this cluster (but really all of the market clusters) by analyzing the data Metrics organizes under its Profile section: static data about each location that provides context about any data collected. This group can also be invited to train other markets in their internal approach.
Group D: Market orgs who “don’t trust data” and/or believe that they don’t have the time or that their community doesn’t want it. They are usually unaware that they ARE collecting data by simply managing market day records.
How to help?
Don’t rush them.
Networks can start with discussions about informal or discrete data (“who’s not here that should be here?” or “Why do some vendors say sales dip when there is an event?” or “How do we know if there are too many markets?”), working to keep a direct loop of collection and use of data. The networks can also help this group by aiding in the development of systems to release these leaders from routine work and to find funding for paid staff. And in many cases these folks are most receptive to other market managers’ input so creating roundtable events to talk about data collection or finding funds to let them travel to another market may help too.
-We know there are other clusters (and outliers too) among markets to be understood in terms of their comfort in data collection, data entry, and data use. This is just a snapshot of one state and only those markets engaging in some manner in their data collection culture.