Scaling Operations Through Data-Driven Technical Assistance

Technical assistance (TA) is a critical support for organizations looking to scale operations safely and effectively. 

Scaling can be incredibly challenging without the right supports and strategies in place.  During times of rapid growth, companies need to accommodate increased demand, adapt to new processes and technologies, and manage monumental change without inordinate disruption—all while staying closely aligned with the mission. 

TA helps build capacity while reducing risk, leveraging niche expertise, engaging key stakeholders, and using data-driven insights to optimize decision-making and resource allocation. 

Data is a key driver of success as it ensures decision-making is objective and not based on emotions, bias, or assumptions. Leveraging advanced analytics, we can track performance and measure impact while gaining the insights needed to refine strategies, improving the potential forconsistent and successful execution.

Leveraging Data for Strategic Growth

Data is crucial to sound decision-making. Proceeding without accurate data or rejecting what the data tells us can easily lead us down the wrong pathways, negatively impacting operational efficiency and potentially derailing plans altogether.

One might think hard data would be difficult to ignore, but it happens. Business leaders deflect or reject inconvenient data all the time because it doesn’t align with their ideas or “how we’ve always done things.” The reality is that we are living in a time of exceptional change and disruption. Assumptions we considered hard and fast facts just a few years ago may have no bearing on what’s happening today. 

Data allows us to see what’s actually happening, allowing us to gauge sentiment and impact and measure key performance indicators (KPIs) of program success.  Leveraging these results, we can apply them in real time to course-correct and keep the process moving forward.

The KPIs you choose to track can vary between organizations and programs, but here are a few you may consider:

• Number of people served

• Program enrollment rates

• Program participation rate

• Volunteer retention rate

• Donation growth rate (for non-profits)

• Website traffic and conversions

• Donor acquisition cost

• Donor retention rate

• Email open rate

• Fundraising ROI

• Employee engagement and productivity

• Employee satisfaction

Tools to track KPIs can include Google Analytics (for monitoring online engagement and other website factors), contextual employee surveys, user surveys, and direct one-on-one conversations with key stakeholders. 

Engaging employees and program users is also critical, as their feedback will inform improvements and reduce friction as you grow, resulting in better programs for all stakeholders. 

Examples of Data Projects and Their Impact

1. Predictive Analytics for Resource Optimization

Predictive analytics helps to align projects with community and public needs. In public health initiatives, for example, data can reveal demographic and growth patterns, which can then be leveraged to inform investment decisions and resource planning to ensure preparedness. It is critical to anticipate future needs as it allows organizations to continuously serve their constituencies as they scale. 

In an impactful example, The Hills Tandem co-architected an initiative to set a new standard in chronic disease care, leveraging more than 73 million data points to enable more personalized care for underserved populations. 

2. Performance Dashboards for Decision-Making

Real-time visualization greatly improves the decision-making process. Global disruption and other variables may impact the direction of their initiatives. Failure to recognize and act upon these insights can result in missed opportunities, so it’s critical to have a simple way to quantify the impact of your efforts. Dashboards pull data from multiple sources, enabling precise insights into what’s working (or not). For example, a sudden plunge in enrollments may lead you to wonder what happened.  

A dashboard details every aspect of your campaign, including any recent changes in pricing, technology, user experience, and online reviews. Without these detailed insights, jumping to conclusions and pointing resources in the wrong direction would be easy. Your dashboard, however, may indicate a specific variable, like a poorly performing sign-up page, that is easily solved with a few design tweaks.

3. Automated Reporting for Compliance and Accountability

Automated reporting significantly reduces compliance risks and improves accountability for key tasks. For non-profits experiencing scale, automated features help to streamline grant reporting and fund tracking, ensuring compliance with grant requirements while enabling more precise funding measurements and forecasting. 

Concerning donor engagement, reporting supports transparency, an essential goal for NPOs as their success relies on public trust and part of that hinges on providing reliable information. People want to know their contributions are making an impact. Without such data, organizations may lose credibility and donor trust. 

THT helped to enhance compliance, optimize data process, and align grant activities to improve outcomes for the Metro Sickle Cell Task Force, implementing key strategies to track program effectiveness, generate insights to support their advocacy, and ensure the task force gained maximum benefits from their funding. 

4. AI and Machine Learning in Operational Scaling

AI and machine learning (ML) help organizations in several ways. Workflow automation supports employees and other internal stakeholders in optimizing their work, accelerating productivity, reducing errors, and assisting people in focusing on higher-value tasks. For example, implementing chatbots significantly mitigates the load on customer service personnel and increases customer satisfaction, as most simple queries can be resolved.

AI makes light work of handling huge amounts of data, helping organizations achieve more accurate insights to inform workforce expansion and service transformation. AI can be implemented to optimize employee scheduling, improve staffing decisions, and driveinternal and external stakeholder satisfaction.

Best Practices for Implementing Data-Driven Technical Assistance

Implementing data-driven technical assistance hinges on three key factors:

• Building a strong data culture within an organization. When people trust that they can solve critical problems using data, they will become intentional about accessing and acting on it. The right tools and strategies help to strengthen the data culture and become part of the organizational DNA.

• Ensuring data quality, governance, and security. Data can be technology or human-driven. In either case, it is essential to ensure data quality, as your insights are only as good as the data informing them. 

• Aligning data initiatives with long-term strategic goals. Clearly define business goals and objectives, establish KPIs to measure, isolate key data sources, and develop a framework to ensure data quality and consistency.

Conclusion

Scale can be sudden or intentional. In either case, leveraging data-driven insights in technical assistance helps organizations accelerate growth initiatives and achieve sustainable outcomes. 

For NPOs and companies experiencing scale, data-driven TA is a methodology that helps build capacity and improve decision-making in every operational aspect.

Speak to us today to learn more about integrating data into your technical assistance strategies.