Speaker 1: Welcome to the lesson on best practices for actionable insights. Actionable insights are patterns that can save resources or unfold opportunities. Ready? Many organizations gather feedback, but often information is neither timely nor actionable. Let us see what techniques can enhance your programs. In this session, we will learn what actionable insight is. We will explore the example of future up skills, and we will also learn about the actionable insights patterns and how to design actionable insights effectively. What is actionable insight? It is that distinct piece of information that helps you implement practical steps toward achieving your targeted goals to grow. Let's take an example of future up skill. It is an organization dedicated to upskilling young adults. Its main goal is to help mid-career professionals navigate the rapidly changing job market. Their training provides the necessary skills to handle challenges in their current job and prepare them for new opportunities. Future up skill also helps employers, businesses to have a skilled workforce fundamental for economic development. In our example organization, future up skills, here, the main activity is skill development training. To achieve our desired outcome, we need to keep an eye on increased student interest in professional careers that are in demand. We can measure the number of students enrolled and those who finished as outputs. The outcome is that participants grow in their current jobs or get new opportunities. Throughout this course, we'll explore this use case. Even if you do not have a complete logic model, it is okay to start with existing data. We will present actionable insights, techniques, and strategies to promote continuous learning. Improving training with insights will fill the skills building gap for real world success. What will use future up skill as our example? Remember that these principles apply to any initiative you're working on. You can use a variety of tools. Select them according to your learning goals and the type of data you have to find distinct patterns. Some useful patterns are performance over time, longitudinal analysis, NPS slash CSAT scores, or pre post change in perception. You may have different data types such as qualitative, quantitative, or multiple languages. How to find and apply these patterns? Let us see it next. So how can future up skill leverage these insights to its advantage? To grow the future up skill insight has to be relevant. Future up skill must find patterns to recognize the job market demands to keep the training valuable. The skills in demand today will be essential tomorrow. Clear. Future up skill must distill complex job market trends into understandable and actionable training programs. Data helps in designing courses that are relevant for learners. Third timely, the job market waits for no one. Future up skill must stay ahead, updating and adapting their offerings based on the latest market trends and technological advancements, ensuring their learners are always market ready. Next specific. Tailored insights will guide future up skill in creating specialized programs that meet the unique needs of their target audience. Understanding the specific career paths and industries their learners aim to enter allows for more focused and effective training. Lastly, the foundation of future up skills strategy should be built on reliable data-driven insights. This ensures that the programs they offer are relevant and timely, but are also trusted and credible. As we move forward, we'll see how these insights can be integrated into future up skills, learning goals, setting a clear path for their success and the success of their learners. As we draw this segment close, let's highlight a crucial strategy for deriving actionable insights. Concentrating on key learning or analytics objectives, a topic we often explore in more detail in subsequent videos, avoid designing a survey or other data without establishing clear learning objectives, neglecting this step can lead you to gather results that are not actionable or offer limited value. Therefore it's essential first to define your learning objectives, craft concise survey questions and test and validate them. Employ feedback analytics tools like SAW packed survey with a small data set to ensure you can analyze genuinely useful insights. If you are not, adjust your pattern and questions. This validation is critical before you expand your data collection or survey efforts to a broader audience. As we wrap up this brief video, I encourage you to dive into a more comprehensive video that delves into various analysis patterns, including quantitative, qualitative, NPS slash CSAT and pre and post analysis. It's important to note that these patterns usually don't stand alone. For a more effective use, combining several methodologies is key. For instance, to grasp the why behind the data, you might start with quantitative analysis, move on to qualitative for deeper insights, and then circle back to quantitative to examine demographics. In specific scenarios, you might integrate pre and post analysis with either quantitative or qualitative methods, so stay tuned and gear up for an engaging journey into data collection and analysis. As we wrap up this chapter, we'd like to recap. We talked about actionable insight, explained it through examples and looked at the different characters of the patterns. Next, we will look at each of them in detail. First, quantitative data analysis. To give you a preview, quantitative data analysis has different segments. Descriptive statistical analysis, comparative analysis, predictive analysis, correlation analysis, benchmarking. Each segment presents a compelling use case and a roadmap to learning objectives. Do you know there is a solution to help you save a ton of hours doing qualitative data analysis and you can use it right now? Simply go to sense.sophac.com and get started. Don't forget to like this video if you found this video informative and engaging and subscribe to our channel for more video like this.