6 Ways to Effectively Drive Analytics Adoption

Data analytics is a topic of increasing relevance and priority for fundraising organizations of any size or sector.

As you explore different analytics pathways, options and solutions, there are common themes around design, workflow and business requirements, as well as important technical, social and cultural considerations, that must be aligned with organizational goals, priorities and expectations.

Ultimately, the value proposition of data analytics is to help 1) improve results and 2) gain operational efficiencies. Despite the simplicity of these goals, data analytics can be challenging to implement and realize at scale for many organizations.

In the following article, we will explore some ways to effectively organize, contextualize and drive analytics adoption efforts within your team, department or organization.

I. Identify Your Purpose

Adoption means change. And change, we know, is hard, as evidenced by the growing volume of research, literature and discussion about the topic of change across various domains and disciplines. Entering a search query of “change is hard” into Google returns nearly 27 million pages to help answer why change is indeed so difficult to achieve. As a side note, the query “change is difficult” alternatively returns about 50 million relevant pages, so I suggest sticking with “change is hard” for the purposes of this discussion.

To drive analytics adoption, be persuasive with your stakeholders. Your stakeholders are your target audience, which includes colleagues, leadership or anyone with a shared purpose and common interest in the outcomes linked to your project work.

To be persuasive, you need to be effective, credible and influential in convincing others to believe and buy into the proposed idea or solution in the first place. A past track record of results or case study highlighting the impact of a similar change effort can be helpful if available. However, you often have limited resources (e.g., staff, funding, tools, etc.) when you are seeking to plan, build and deploy solutions under time pressure.

To convince others quickly, clearly articulate what you intend to accomplish in relatable terms that strongly appeal and align with your stakeholders’ needs. In a similar way to developing an elevator speech, it is useful to develop a “project pitch” or “purpose statement” for your projects.

Once you have identified and translated the purpose of your project into a clear and succinct set of messages, develop a plan to cultivate interest and engagement with your stakeholders to foster adoption. Otherwise, your projects run the risk of sitting on a shelf and becoming just another good idea whose potential value and impact may never be realized.

II. Create Adoption Pathways

There are many ways to drive analytics adoption within your team, department or organization.

Here are 10 adoption pathways to launch the delivery of your analytics solutions:

  1. Identify challenges, opportunities and solutions.

    Conduct a SWOT analysis, stakeholder interviews or survey across a selection of functional areas to gather requirements and document existing challenges. The challenges or “pain points” represent opportunities for potential solutions. Seek to understand and define how these solutions can add value to your organization. Keep organizational priorities in mind to ensure alignment, buy-in and support for potential solutions.

  2. Prioritize solutions into a roadmap.

    Select and prioritize your projects based on current resources (e.g., staff, capital, systems, expertise, time, etc.) and potential value (e.g., competitive advantage, opportunity cost, operational efficiency, etc.). Create a roadmap, which is a plan or blueprint that defines success and outlines project deliverables (e.g., why, who, what, how, when and where). Document your roadmap and hold yourself accountable to your projected timelines and promises to others. Deliver “quick wins” early to build trust, interest and momentum toward future projects.

  3. Establish context and purpose.

    Create your why statement or “project pitch.” In other words, make sure you can articulate “what’s in this for you?” and how your target audience will benefit from your solutions. Consider providing context and rationale, especially for initiatives with broad impact and potential changes to existing workflow and procedures.

  4. Translate solutions into stakeholder-centered language.

    Know your audience. Development officers and operations staff can have different business needs, perspectives and preferences when using CRM tools, reporting systems and analytics solutions. For front-line users, avoid jargon, complex terminology and excessive technical detail whenever possible. Instead, use plain language that describes how the tool or solution can be used for decision support, actionable insights and workflow enhancements.

    To facilitate adoption, use language that is consistent with stakeholder knowledge, familiarity and workflow expectations. If you identify multiple names for similar tools (e.g., prospect list, portfolio snapshot, etc.), develop and promote shared terminology within your team and beyond.

  5. Focus on form and function when delivering solutions.

    Focus on both form (“look and feel”) and function (“how things work”) when designing, testing and delivering solutions. In addition to the functional and business requirements of your project specifications, pay attention to the deliverable format and use fonts, headers, formatting, colors, logos and graphics that are consistent with your organizational identity and brand.

  6. Socialize solutions with early adopters.

    Build and develop a list of early adopters, potential champions (i.e., those who share enthusiasm for your analytics solutions) and difficult customers. Identify adoption strategies for each audience group and cultivate meaningful partnerships through discussion, brainstorming and presentations.

  7. Solicit regular feedback.

    Feedback is a powerful tool that can help guide enhancements and prioritize future improvements. Solicit feedback regularly and document your findings. Communicate with your stakeholders as you implement improvements based on feedback to inspire trust and create honest feedback loops.

  8. Start where you are.

    To drive analytics adoption, accept current organizational realities and draw on lessons learned. Start where you are. Document the “current state” as well as the desired “future state” of your analytics roadmap. Once you have a plan, you greatly increase the odds of transforming ideas into tangible deliverables, action and reality.

  9. Build a community of support.

    Build a “think tank.” Convene a brainstorming meeting. Invite thought partnership from colleagues. Get involved in a listserv or online forum discussion. Explore a volunteer role with Apra! You do not have to know everything, but you should at least have a long-term and short-term vision of what you want to accomplish and seek expertise within your communities to help.

  10. Be a learn-it-all, not a know-it-all.

    Take on a new project. Build a prototype. Research industry trends. Take an online course. Be committed to lifelong learning to expand your skills and perspective. For more information on opportunities to expand your professional knowledge, check out Apra’s Body of Knowledge.

III. Start Where You Are

There are opportunities to apply analytics solutions if you look carefully within your organization. Start simple. Take an existing report and solicit feedback to identify potential improvements and ways to creatively integrate analytics into stakeholder workflow.

Example Use Case:

  • Development officer is reviewing portfolio and needs to identify which prospects to reach out to first.

Example Solution – Prospect Management Report with Baseline Features:

There are many possible solutions to help development officers prioritize which prospects to reach out to first. Attached is an example reporting tool:


Workflow Evaluation:

Here is a summary of example workflow analysis: 

  • The conventional prospect management report example contains useful information, such as stage of readiness, days in stage, wealth rating, affinity rating, constituent type, etc.
  • From a prospect management view, the stage of readiness, wealth rating and affinity rating are useful tools for helping prioritize prospect outreach and follow-up.
  • For example, a development officer could sort or filter by stage of readiness to identify all prospects in stage “qualification” who require an email invitation, call or visit to discuss their philanthropic interests and priorities.
  • Similarly, a development officer may choose to filter by wealth rating and craft cultivation and solicitation strategies based on this information.
  • Utilizing “Preferred Class Year,” a development officer may opt to invite prospects to specific reunion year events and engagement opportunities.
     

Decision Support Framework:

  • The traditional model of a portfolio is a list of prospects with various constituent information, bio/demographic detail, prospect management detail (e.g., fundraiser role, stage, strategy, last contact, etc.), wealth rating, giving information, etc.
  • While useful, the conventional prospect list would benefit from the inclusion of a decision support framework guided by data analytics.
  • Decision support, in this context, refers to actionable insights, workflow recommendations and next steps guided by data available within the organization.
  • As we shift from descriptive to predictive and prescriptive models of portfolio and prospect management, we focus on lines of inquiry related to portfolio strategy and activities that lead to target outcomes.
  • Focusing on decision support, a portfolio can transform from a conventional list of prospect names to a list of relationship-driven opportunities that require strategy, planning, activity, decisions and next steps.

IV. Solicit Feedback

As outlined in the adoption pathways in section 2, soliciting feedback is a useful way to drive enhancements and analytics adoption. Here is a list of example feedback and questions organized by data requirement and priority:

V. Deliver Solutions

Revised Solution – Prospect Management Report With Decision Support Feedback:

Analytics adoption is a continuous process. To drive analytics adoption, deliver solutions and enhancements that meet stakeholder requirements. The purpose of the prospect management report is to help development officers prioritize which prospects to reach out to first. Attached is a revised report tool with decision support feedback features:

Workflow Enhancements:

Here is summary of example workflow enhancements:

  • A development officer can use lifetime giving thresholds (e.g., $5k and above) to guide stewardship, recognition opportunities, special event invitations, board recruitment, etc.
  • In a diagnostic way, a development officer can use number of years of giving to guide recognition opportunities and planned giving strategy.
  • A development officer can prioritize outreach by filtering on “Strategy Entered” (Yes or No).
  • If prospects are both alumnus and parent constituent types, development officers can tailor outreach and messaging to reflect both types of connections to the organization:
         o    “Preferred Class Year” can be used to invite prospects to specific reunion year events and engagement opportunities.
  • If days since last contact date > X (e.g., 90 days), this can prompt actionable insights:
         o    No contact information or need updated work phone and email?
         o    Development officer needs to update contact reports?
         o    Development officer needs to reach out to prospect?
  • If days in stage > X (e.g., 365 days), this can trigger alerts or reminders:
         o    Development officer to update stage?
         o    Development officer to revise prospect strategy?
         o    Development officer to consider prospect re-assignment?
  • Shifting from descriptive to predictive analytics, a development officer can use “giving inclination” scores or tiers (“A”, “B”, “C”, etc.) based on predictive modeling indicators developed via vendor and/or in-house.

VI. Stay Connected

Data analytics provides the opportunity to improve outcomes and gain operational efficiencies.

To effectively drive analytics solutions within your organization, identify your purpose, translate solutions into stakeholder language and create adoption plans focused on your audience’s goals, workflow and needs.

Start small, gather requirements and prioritize the delivery of enhancements based on user feedback. Above all, keep your promises to build a platform of trust, collaboration, advocacy and adoption of useful analytics solutions.

For more on developing ways to pitch your ideas and organizational contributions, check out the newly released Apra Advocacy Toolkit.

 


Rodger Devine is the senior executive director of business intelligence at the Dornsife College of Letters, Arts and Sciences at the University of Southern California in Los Angeles, where he oversees data analytics, information strategy, advancement operations, gift and data administration, gift proposal development, and leadership annual giving programs. Rodger completed his graduate studies in information, analysis and retrieval at the University of Michigan, where he was also a member of the Michigan Data Sciences team and co-founder of the Student Organization for Information and Retrieval. He serves as a faculty volunteer for Apra OverDRIVE/ 2018, bringing more than 15 years of higher education experience in enterprise information systems, software engineering, organizational development and cross-functional leadership. He has presented at Apra and DRIVE/ conference on topics related to prospect management, analytics adoption and organizational leadership.

Rodger is a faculty member for OverDRIVE/ 2018, a one-day deep dive into the world of analytics that takes place on Feb. 26, 2018, one day before the DRIVE/ conference. You can view the full schedule here. Rodger will also be presenting a machine learning lab at the DRIVE/ Conference on Tuesday, Feb.27, 2018, which you register for here.

Connect with Rodger via email, LinkedInblog or check out his upcoming book Data Science for Fundraising: Build Data-Driven Solutions Using R, which will help you learn how to solve fundraising problems using various data science techniques and machine learning methods using step-by-step R recipes.

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