Learning the INFORMS Analytics Framework (IAF): The Proven Guide to Developing Analytics Solutions

the IAF, ensuring that analytics efforts align with organizational goals. This domain involves defining the business problem or question clearly and concisely, without focusing on technical specifics. It requires identifying stakeholders and obtaining their alignment on the business objectives and intended outcomes. As Johan Bos-Beijer noted, "Defining the business problem or question is the most important critical activity in any analytics initiative." This step is key to avoid the common pitfall of analytics efforts failing due to poor alignment or unclear objectives. By establishing a clear business case, organizations can ensure that analytics is applied to solve the right challenge, ultimately leading to successful outcomes.

Analytics Problem Framing

Once the business problem is defined, the next step is to determine if it can be reframed as an analytics problem. This involves assessing whether analytics is the appropriate approach and identifying the type of analytics problem, such as optimization or classification. Nicholas McMillan emphasized the importance of this step, stating, "If the business problem can't be reframed as an analytics problem, your next question is what kind of analytics problem is it?" This domain sets the stage for methodological development and ensures that analytics efforts are focused on problems that can be effectively addressed through data-driven solutions.

Data Management

Data management is a vital domain that requires significant effort and attention. It involves understanding the data environment, including ownership, constraints, and potential privacy concerns. As Johan Bos-Beijer highlighted, "Ultimately, any analytic solution is dependent on data." This domain requires comprehensive data documentation and inventory practices to ensure that the solution is reliable and trustworthy. It also involves assessing data quality and determining any missing data that may be needed. Proper data management is essential for supporting the analytics solution and ensuring its success.

Methodology Selection and Model Development

Methodology selection and model development involve choosing the appropriate analytical techniques and building the solution. This domain requires evaluating and selecting methods based on the nature of the problem, available data, and organizational resources. Aiden Dumas explained, "Creating the actual solution is just one of seven domains that occupy roughly the same amount of time." This step involves building, testing, and refining models to ensure they are valid, scalable, and actionable. Proper documentation and communication are crucial to ensure that the solution is understandable and justifiable to both technical and non-technical stakeholders.