Where are you on the path to making more informed, data-driven decisions? Have you identified the metrics? Do you have the right people? And most importantly, do you trust your data?
We live in an era where access to technology and data are at our fingertips, literally. But when we begin diving into adoption and the process of setting up system to derive business insights from customer and operational data points, most organizations are far from comfortable. According to the Harvard Business Review’s 2019 Big Data and AI Executive Summary 77% of executives site adoption as a major challenge.
Regardless of where your organization is in that process, our Data Analytics Playbook can help your organization set the stage for more informed decision making. Here’s how we do that.
Step 1: Understanding metrics – We start by talking about the importance of translating core business goals into metrics. Not only will this help to create organizational alignment around a set of goals, but it also helps leadership measure whether day to day activities are actually moving the needle.
Step 2: Leveraging business analytics – From there, we move into application. Data isn’t a key that unlocks change. People from within your organization need to become familiar with this cultural shift in decision making, establish trust around this new process and collaborate on a common language around what the numbers mean and how best to apply them. It takes time and patience.
Step 3: Improving data quality issues – Data is only relevant when the information conveyed is accurate. As we establish new decision-making processes, this is a great opportunity to make sure the information you’re collecting is accurate, and to establish quality control mechanisms to carry your program into the future.
Step 4: Planning for AI – The concept of AI feels big and scary, especially for those in the early stages of this process. In this section, we establish a realistic path to AI and how organizations can chart their long-term objectives with a progression plan toward AI, and a little bit of patience. Included in this section is a mini case study featuring a Fortune 200 insurance company going through this process.
Step 5: Putting It All Together – This section breaks down some popular programming languages and how to elevate your practice to the next step, machine learning.
It’s as simple as that. Well, really, we know the journey to maturing your business analytics program isn’t simple or easy. But our goal is that The Data Analytics Playbook provides the necessary context to help you take the next step. Make sure to download the complete report here.