Use Data for Better Decision-Making
We Can’t Always Predict the Future, but with Data, We Can Try
Constance DeVereaux, Ph.D.
The biggest trend in leadership studies these days is training future leaders in the skills of good decision-making. According to Decision-Making Strategies for Leaders, “decisive leaders stand out.” In the words of another source, leaders can expect “increased pressure” in the future to make quick and “effective decisions in an increasingly ambiguous environment.”
But, how do you know you’ve made a good decision when ambiguity prevails and huge uncertainties or wildly competing values abound? Overly quick decisions can be disastrous if you are prone to hasty conclusions or operate from bias.
Can reliable, consistent, and good decision-making be taught?
Over roughly the past 20 years, I’ve trained arts leaders to do just that. What I’ve found is that teaching the rules of reasoning and decision-making aren’t enough. According to the London Business School, developing “decision-making confidence requires sophisticated skills, knowledge, and experience.” That means that good data and the experience to combine both skill and knowledge are what lead to results.
Although some sources may tell you otherwise, one problem with decision-making is what counts as good is often only clear after a decision is made and we see the outcome. Suppose you want to increase audiences for your opera company. You decide to provide field trip buses for school kids to attend special weekday performances with their teachers. All good so far. But then your city has a bus strike in the first week of school, just as your project was set to launch. Oh, and the contract you signed doesn’t have a provision for unforeseen events like this one.
What looked like a good investment of organizational time and resources before doesn’t look so good now.
What’s a decision-maker to do? Adding to the problem is that the world (by which I mean your boss, your donors, and your board of directors) is not always forgiving when things go awry. Never mind that it seemed like the right decision at the time.
If only you could predict the future.
In a sense, you can. Or you can come very close if you are able to anticipate outcomes. The ability to project using good data is a skill that every arts manager needs. The expression “doing your homework” means that you take the time to gather evidence (lots of it) before coming to any conclusions that impact your organization’s time, money, and resources.
In the above case, suppose you had known that every year for the past five years, local bus drivers went on strike in the first week of the school year. In this case, you might have anticipated it would happen again and devised a plan that didn’t rely on buses, or that started later in the year.
More sophisticated decision-making uses data analytics and data intelligence to understand trends and to make projections. Arts leaders can take advantage of large scale data sets, or big data, for strategic planning in a wide range of decision-making areas. Big data is increasingly used to make economic, cultural, social, and policy decisions, even in the case of mid-size organizations. It’s not as intimidating as it sounds.
Data is factual information used for the purposes of reasoning and decision-making. The data, or information, can be in any form—spoken, written on paper, or even cut into stone, as it was in ancient times.
In the digital age, data refers to information in digital form. Aggregated digitized data is especially useful for decision-making that relates to strategic and long-term projections in areas like fundraising, donor prospecting, marketing, and creative district planning.
Data intelligence is the use of data in meaningful ways to gain deeper understanding about an area of interest. For example, you might use information gathered from past events and circumstances in order to help you understand trends and outcomes that either turned out well (so may want to capitalize on them in the future) or that turned out poorly (leading you to plot a new strategic direction going forward).
Data analytics help you make calculations about the future. Although no prediction can provide absolute accuracy, data projections help in setting a reliable and evidence-based plan in motion.
Let’s imagine that your organization will participate with city planners in fact-finding and report writing to support live/work space for artists. Knowing that the number of visual artists in your city has steadily increased over the past 10 years and that their average income is currently under the poverty level might be useful for both planning and advocacy. True, you could go out and gather the information on your own. But it is time-consuming and costly—assuming you have the skills to do it accurately. Or you could make use of existing, aggregated data, which will allow you to generate reports quickly and accurately, targeted to your area of interest or need.
Making Use of Aggregated Digital Data
Aggregated digital data like the data found in WESTAF’s Creative Vitality™ Suite (CVSuite™) have high value for the following reasons:
- Someone else did the work of gathering lots of data together so that you don’t need to. CVSuite provides you with accurate information relating to the arts and creative industries in the U.S. (you can choose state, county, metropolitan statistical area (MSA), or ZIP Code level data).
- Having a lot of data can help you make better decisions. There is a common reasoning fallacy called Hasty Generalization, where we leap to decisions without enough data or try to solve problems using anecdotal evidence. That happens when you base your decisions on personal experience or the limited information you have on hand. Instead, aggregated data provides you with information beyond what you can typically access on your own.
- A user of the CVSuite tool can make comparisons over time that might not be possible otherwise. For example, the data in the tool can show how many artists currently live in your city and what their average income is. That information alone won’t show you an increase in the number of artists over time unless you have that historical data too, which the tool can show. With the right data set, you may also be able to make comparisons between cities or compare the incomes of artists versus non-artists, if that data is relevant to your cause.
- It helps to understand the relationship between different sets of information. In the above example, you want to know the number of artists as well as their average income over time. Reports generated from a large data set make it easy for you to see the relationship between the two. And if average income is increasing or declining, you might want to know why. A data set that includes such things as average age, marital status, home ownership, or other information, will allow you to build a picture of the life of artists in your city based on the information the set includes.
I’ve only listed some of the many advantages of using aggregated data in arts organizational decision-making. My example explains how data-driven projections can be used for developing live-work space for artists in creative district planning. It allows you to develop a comprehensive picture of artists’ lives in your community. Aggregated data sets can also help in planning and decision-making in the areas of economic impact forecasting, marketing, donor prospecting, audience development, program development and design, advocacy, and many others. While both skill and experience are needed to turn arts leaders into better decision-makers, neither is enough without good data. In an increasingly data-driven world, familiarity with data-based-decision making is imperative.
If you are interested in using CVSuite in the classroom, contact the CVSuite team at firstname.lastname@example.org.