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Better Decision Making Through Analytics
This document summarizes a presentation on using analytics for better decision making at nonprofit organizations. The presentation discusses how nonprofits currently use some basic analytics like budgets and dashboards but have untapped potential to use data more extensively. It identifies common challenges to data utilization as collecting quality data, lacking expertise, technology and prioritizing time and money for analytics. The presentation provides examples of how benchmarking reveals data gaps and inconsistencies between systems. It emphasizes the value of tracking program and outcome data and client information.
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Better Decision Making Through Analytics
- 1. Better Decision-Making Through Analytics JCC Association Executive Seminar 2013 Brian Hayden Collaborative Strategies, Inc. © 2012 | www.getcollaborative.com 1
- 2. Agenda! ! CurrentContext! ! Why Analytics Matter! ! Applications! ! Getting to the Next Level! ! Summary! © 2013 | www.getcollaborative.com 2
- 3. output from themachine, or even actively prevented it. In a number of cases, the processes—the machine itself—were not strategically designed and thus no amount of data input could help to create better Relevant Factors! decisions. The Data Machine Inputs Financial and Expertise Prioritization Money Technology Operations Data of Time Internal Marketing, Factors Communications and Fundraising Data Programs and Outcomes Data External Data Data- Driven xternal External Funder Funder Decision Factors Requirements Support Making © 2013 | www.getcollaborative.com A well-functioning nonprofit data decision-making 3 process provides numerous possibilities for nonprofits to
- 4. Definition! Source: Competing on Analytics! What’s the best that ! Optimization! can happen?! Predictive modeling! What will happen next?! Forecasting/ What if these trends continue?! Competitive advantage! extrapolation! Statistical analysis! Why is this happening?! Alerts! What actions are needed?! Query/drill down! Where exactly is the problem?! Ad hoc reports! How many, how often, where?! Standard reports! What happened?! Degree of intelligence! © 2013 | www.getcollaborative.com 4
- 5. It Doesn’t Haveto be Calculus! ! You ARE using data to make decisions if you:! ! Have and review a budget! ! Use a dashboard to communicate results to your board! ! Track click-through rates to web and email campaigns! ! Track early childhood or camp utilization rates! © 2013 | www.getcollaborative.com 5
- 6. But the Potentialis Far Greater! ! JCCs have a wealth of data… but it’s all over the place. ! ! Dedicated systems (membership, fundraising, financials)! ! Excel spreadsheets! ! …! ! Like most organizations, JCCs collect a lot of data that doesn’t get analyzed.! ! Like most not for profits, JCCs tend to under-invest in technology.! ! The right skills aren’t on the team. ! ! Analytics is no one’s job. ! ! No one has time. ! © 2013 | www.getcollaborative.com 6
- 7. Analytics - RealTime!! https://www.surveymonkey.com/s/jcca-es! ! ! (Answer first 3 questions, click next, then stop.)! © 2013 | www.getcollaborative.com 7
- 8. Biggest Challenges toUtilizing Data! he following section explores these challenges in greater detail. 30% 25% 27% 20% 24% 23% 22% 15% 10% 5% 6% 0% Data Expertise Technology Prioritization and Money Collection/Quality Time ata Collection Source: Nonprofit Technology Network! he ability to collect and work with data is a barrier reported by many nonprofits. In the course of the urvey, © 2013 | www.getcollaborative.com 8 we asked specific questions about organizations’ abilities to collect data on programs and on
- 9. What We’ve Seenin Benchmarking! ! System A doesn’t talk to system B. ! ! Example: Closing a membership sale from a tour.! ! There are lots of holes, sometimes in surprising places. ! ! © 2013 | www.getcollaborative.com 9
- 10. Tracking Programs andOutcomes Tracking program and outcome-related data should be the bread-and-butter for nonprofits because it’s one of the best ways to articulate what they are delivering and the extent to which they are delivering on their mission. However, fewer Not-for-Profit Community! were measuring information about The Larger than two-thirds of survey respondents said they programs in which their clients or constituents take part, and just half reported tracking information about client or constituent outcomes. 90% Tracking Finding it Useful for Spending or 80% 89% Budgeting Decisions 85% Finding it Useful for Programming 70% Decisions 73% 60% 50% 59% 59% 49% 50% 49% 40% 41% 30% 20% 10% 0% Your financial actuals vs budget Information about what programs Information about outcomes specific clients/constituents take part in of clients/constituents The ones who are tracking this information find it useful for making decisions about programs, and most of Source: Nonprofit Technology Network! them find it useful for budgeting purposes as well. 10 As the focus groups showed, the range of programmatic data that nonprofits track runs the gamut of © 2013 | www.getcollaborative.com
- 11. so—44 percent ofthose respondents report that they do not have the technology to do so, while 41 percent report they lack the time and/or money. Marketing, Communications and Fundraising Data While many nonprofits are tracking various type of marketing, communications and fundraising data—what we refer to as “outreach” data—our survey indicated a surprisingly low number are actually using that data The Larger Not-for-Profit Community! to make decisions. 80% Tracking this Metric Finding it Useful for Spending or 70% Budgeting Decisions 71% 69% Finding it Useful for Programming 60% Decisions 50% 56% 48% 40% 44% 30% 20% 23% 39% 17% 26% 17% 10% 12% 11% 7% 8% 9% 0% Number of people on Number of new Number of visitors to Number of comments Number of people your mailing list donors in the past your website you receive on who open emails that year Facebook you send out N= 396 Source: Nonprofit Technology Network! Among this outreach data, metrics related to fundraising performance—such as the number of new people added 2013anwww.getcollaborative.com © to | organization’s mailing list or the number of new donors—are tracked by more than two-thirds of 11
- 12. Agenda! ! CurrentContext! ! Why Analytics Matter! ! Applications! ! Getting to the Next Level! ! Summary! © 2013 | www.getcollaborative.com 12
- 13. Why Measure?! To Rationalize:! To Inspire:! ! ! • Transcend politics! • To tell a story! • Prove value! • To reassure ourselves! • Improve efficiency! ! • Improve ROI! • What gets measured gets managed! Source: Performance Measures and the Rationalization of Organizations! © 2013 | www.getcollaborative.com 13
- 14. Funder Perspective! ! Jim Collins: You want people to give you money because you are good – not because you need it. ! ! Donors want a (social) return on their investment. Can you demonstrate outcomes?! © 2013 | www.getcollaborative.com 14
- 15. What’s the PrivateSector Doing?! ! Capital One runs 300 experiments a day on new product initiatives.! ! Progressive Insurance offers lower rates to drivers willing to install real-time monitors in their cars. ! ! Retailers of all varieties are pushing loyalty cards on customers to monitor their habits. ! ! Amazon uses past purchases to show you advertisements for other products you might like. ! ! Location-based advertising is one of the fastest growing segments of marketing.! ! And…! © 2013 | www.getcollaborative.com 15
- 16. Why?! ! Beyondintuition! ! Creating transparency! ! Enabling experimentation to discover needs, expose variability, and improve performance! ! Segmenting populations to customize actions ! ! Supporting (or replacing) human decision making with automated algorithms ! ! Innovating new business models, products, and services ! Source: McKinsey! © 2013 | www.getcollaborative.com 16
- 17. Agenda! ! CurrentContext! ! Why Analytics Matter! ! Applications! ! Getting to the Next Level! ! Summary! © 2013 | www.getcollaborative.com 17
- 18. • Greater revenue! Objectives! • Lower cost! • Higher satisfaction! Participation Analytics! Beginner! Advanced! • Cross-selling! • Identification of members most at risk of cancelling! • Exchanging lists with other community • Targeted marketing! organizations! • Discounting/promotional optimization! • New member acclimation! ! ! ! © 2013 | www.getcollaborative.com 18
- 19. • Greater revenue! Objectives:! • Greater retention! Philanthropy Analytics! Beginner! Advanced! • Campaign analysis! • Cross-referencing members and donors! • New/lost trends! • Lapsed donors! ! • Moves management! • Third party research tools! ! ! ! ! © 2013 | www.getcollaborative.com 19
- 20. • Resource optimization! • Strategic direction! Objectives! • Compelling communications! Outcomes Analytics! Beginner! Advanced! • User surveys! • EC: Kindergarten readiness tests! • The JCC Benchmarking Project! • Senior Adults: mental and physical wellness tests! ! • Longer-term Jewish impact?! ! ! ! © 2013 | www.getcollaborative.com 20
- 21. Case Study: The“Value Matrix”! Financial Results! Non-Financial! Direct! After Participation! Outcomes! Unmet Allocations! Need! Grade! Program 1! Program 2! Program 3! Program 4! © 2013 | www.getcollaborative.com 21
- 22. • Identify topperformers! Objectives! • Succession planning! • Optimize training! Talent Analytics! Beginner! Advanced! • HR database ! • 9-box talent planning! • Performance Reviews! • Extend HR database to include skills and training! • 360 Reviews! ! ! ! ! © 2013 | www.getcollaborative.com 22
- 23. Case Study: 9-BoxTalent Planning! 5 Expectations Exceeds High Exceptional Top Talent Performer Performer 4 Performance! Expectations 3 Achieved Solid Key Rising Talent Performer Performers 2 Development Needs Lower Inconsistent Under Rating 1 Performers Performer Developed . Level 1 Level 2 Level 3 Potential! © 2013 | www.getcollaborative.com 23
- 24. • Right skills! Objectives! • High engagement! Board Analytics! Beginner! Advanced! • Skills/background matrix! • Periodic assessments! • Fundraising involvement! ! ! ! ! © 2013 | www.getcollaborative.com 24
- 25. Agenda! ! CurrentContext! ! Why Analytics Matter! ! Applications! ! Getting to the Next Level! ! Summary! © 2013 | www.getcollaborative.com 25
- 26. Two Paths! Business Strategy! Data Strategy! © 2013 | www.getcollaborative.com 26
- 27. Business! Data! Culture! ! Analytics is a decision-making culture. Culture starts at the top… with you. ! ! What expectations are you setting regarding decision criteria? ! ! How is this trickling down the organization? ! ! Doesn’t mean YOU have to be a PhD in advanced mathematics. ! ! Don’t make analytics “one more thing”. Integrate it into existing decision-making processes.! © 2013 | www.getcollaborative.com 27
- 28. Business! Data! Planning Your Strategy – Where to Start! • Understand your performance drivers.! 2 1 !Yes! • Take it in stages. ! Data easy to get?! • Quick wins are ! important.! • Better to capture less ! data and actually DO 2 No ! something with it. ! ignore • Team: Leaders from program, IT and finance; use lay talent No ! ! ! !Yes! when available! High Impact?! © 2013 | www.getcollaborative.com 28
- 29. Business! Data! Expertise! ! Every manager doesn’t need to be an Excel wizard. But every manager should appreciate the use of data to inform decisions. ! ! Do you have sufficient quantities of analysts?! ! Make the necessary training available. ! ! Consider analytical abilities in future hires.! ! This isn’t just about your staff. Who on your board can help with strategy? Include analytics on your board skills matrix.! © 2013 | www.getcollaborative.com 29
- 30. Business! Data! The Role of the Data Champion! ! Someone has to champion “good data” throughout the JCC. ! ! This doesn’t have to be a dedicated IT person.! ! The days of managing IT as a utility are gone. ! ! Data (and IT) can be strategic differentiators and should be managed accordingly. ! © 2013 | www.getcollaborative.com 30
- 31. Business! Data! Your Data Strategy! You Know You’ve Made it When:! ! Figure out what you have. Clean it up. ! • Staff spend more time ANALYZING data than ! Based on your strategy, what don’t COLLECTING it. ! you have that you need?! • Staff never argue over ! Standardize your definitions (e.g. whose data are more accurate. ! when do you consider a membership “cancelled”)! • Staff that need data access have it (directly).! ! • Hypotheses can be quickly tested without an inordinate amount of manual manipulation. ! • Reports include data from multiple sources.! ! © 2013 | www.getcollaborative.com 31
- 32. Low Hanging Fruit:The Benchmarking Project! ! Cultural reinforcement! ! Creates good habits! ! Low cost! © 2013 | www.getcollaborative.com 32
- 33. Questions? © 2012 |www.getcollaborative.com