Many association professionals have a “love AND hate” relationship with data and research. While they recognize its importance in providing insights for decision-making, they may also feel overwhelmed by the challenge of collecting, understanding and interpreting information. However, while incorporating data into your management approach does not need to be difficult or expensive; it does require forethought and planning, and sensitivity to the organization’s culture around decision-making.
Working Within a Cultural Framework
All manner of data is now widely available to individuals and organizations. It can be gathered inexpensively from a myriad of secondary sources (e.g., government statistical portals, social media or universities) or the association database, or the association may directly collect it for the sake of answering specific questions (e.g., through surveys or interviews). Most associations tap into one or more of these sources, but many also forgo these valuable opportunities because they lack an organizational culture that supports data-driven decision-making. A loose typology of associations is presented below to identify how best to fit data into your organization.
Type 1, the “Data-Disdaining” Association: Associations that fall into this category tend to avoid the use of data, sometimes this is due to a lack of comfort in the underlying meaning of the information, or, they may simply have a culture that is more oriented towards using instinct and experience for decision-making. It is important to note that the strategic and tactical decisions made in these organizations often rely on the anecdotal experiences of volunteers and staff, as well as their experiences with those in the industry. Out of all groups in the typology, the “data-disdaining association” may have the most to gain from research and data. These associations frequently come around to the need for data to help validate a major decision facing the organization.
To make the most of their efforts, staff in data-disdaining organizations should be sensitive to the stakeholders involved in data and research utilization. They may benefit from paying greater attention to initial planning, including the critical decision of how best to obtain “buy-in” for any research that needs to be conducted. Often, involving important individuals or groups at the beginning of the process can help to fully explain the steps that are required, guarantee that trust is established and can assist in providing support for the outcome of the effort – ensuring that any data collected is utilized to its fullest potential.
Type 2, the “Data-Informed” Association: Most associations fall into this category of a data user. These groups tend to conduct research occasionally, either as part of a defined timetable (e.g., they conduct a “needs assessment survey” every three years) or on an “as needed” basis (e.g., in order to inform the Board of Directors or staff as part of a planning or goal-setting process). They may use the data and research purposefully, or as an afterthought, but they tend to value it as a decision-making tool and tap into it as needed. Data-informed associations place merit on objective information, but may not have a well-defined data strategy. This could be the result of a lack of staff expertise or capacity, or simply because the Association has not yet prioritized the need to map out their existing and future data requirements in order to meet their information needs.
These types of associations may benefit from conducting an initial assessment of the return-on-investment of their data efforts. It is helpful for these organizations to identify what types of information have helped them in the past, how they have used or not used that information and whether they tend to lack key data points, trends or other information that would be helpful to association management and leadership. This initial review of their work and data usage will help staff to identify and more fully appreciate the confidence that data creates and the insights that research is capable of producing. Perhaps most importantly, taking stock of past research efforts is an integral part of the continual process improvement that should not be overlooked – it will make it possible to plan incremental or substantial changes to the research program to fully capitalize on available resources.
Type 3, the “Data-Driven” Association: Associations in this category tend to have clearly defined data collection plans and strategies, and rely on data as an integral part of their decision-making. These groups may devote greater staff and financial resources to their data collection efforts, and benefit from having empirical evidence at their fingertips when making decisions. Unlike “data-disdaining” and “data-informed” associations, “data-driven” organizations typically have a high awareness of their knowledge of the association and the industry that it represents – including the ability to distinguish between what knowledge is strongly supported by empirical evidence and what is based on assumptions and anecdotes.
Data-driven associations have a culture that is conducive to making the most out of their data and research efforts. They devote resources, staff and organizational energy into maintaining a plan for data collection to ensure that staff and leaders have the information they need. Data-driven organizations may benefit from documenting or curating their knowledge, such as by capturing, presenting/sharing and updating the most important data points in an online dashboard. Not only will this help to share knowledge and understanding across the organization, but it will also facilitate the development of new research questions as information users pinpoint new information needs.
Data has never before been so widely available to associations. However, the key to its effective utilization frequently hinges more on the organization and its comfort level with research than it does on the expensive or difficulty of data collection itself. An understanding of organizational culture can help your association make the most of data and research as a management tool.
If you are interested in learning more about data strategy, please contact Patrick Glaser at email@example.com.