Inquiry Response: Three Things Your Operational Efforts Might Be Missing

By IIA Expert, Mar 30, 2020

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We want to improve our operational analytics efforts starting with high-level skills, pipelining, and structure. We have a hub-and-spoke model and analytics teams in place. What is missing from our internal conversations?



  • Consulting mindset
  • Pipeline as a chunking process
  • Organizational network analysis


One skill that often gets overlooked is that of the consultant. Promote a consulting mindset so that:

  • The team members learn how to understand the challenges from the business perspective and to pose questions so that business stakeholders get the sense that they’re being understood.
  • You promote conversation and collaboration between the business and analytics teams. In an old-fashioned transactional environment, the stakeholder poses a question and the analyst retreats to generate the answer. Instead, the business should be involved through the entire process.
  • You educate the team about the art of storytelling with data. Encourage data scientists to think about their work as a journey rather than a series of inputs and outputs. How would they tell this story to a friend?

Working with the business allows your team to show results as they go, rather than face potential rejection if the business doesn’t like the final end results. Mandate that team members spend at least half a day with the business area they working with.


The output of a process in which the data scientists collaborate with the business is a series of questions that both data scientists and business folks can relate to. This is the start of your pipeline.

  • Refine the pipeline by breaking the questions down into sub-questions. They’ll still be framed as business questions.
  • Explore the sub-questions by asking yourself how analytics can support answering them. Keep breaking down the questions until they’re small enough that you can answer them analytically and you know what the data needs are.
  • If the questions are small enough, you can estimate their return value, which will help you with prioritization.

One of the benefits of this pipeline process is that you always have line of sight back to the business question. In addition, you can cut your losses early if you’re not seeing a return value.


Organizational network analysis allows you to analyze the informal networks that exist within an organization. People don’t naturally work only within the formal hierarchical structures. They seek out the people who can best help them with particular questions, challenges, and advice.

  • The result of the analysis is an understanding of who you can team up. For example, you can partner people who are on opposite ends of the spectrum, such as a communicator who can tell stories with a highly analytical data scientist.
  • As your pipeline grows, you will need expertise that resides outside the analytics hubs, and you will naturally move into using more of the informal network in what is often called a networked community model. Think in terms of communities rather than spokes.
  • You can network people who have the skills you need but who reside in the businesses. Bring them together for problem solving across areas or stand them up to work on certain questions when you need excess capacity.

Organizational network analysis is powerful because you can identify skills that are remote from where your team sits, and you can build relationships with these people in a way that you wouldn’t normally be able to through a traditional structure.

About the author

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IIA’s Analytics Expert Network is a global community of analytics practitioners, thought leaders, and subject matter experts. Clients leverage the Expert Network to gain independent insights to solve their current challenges via IIA’s Inquiry Service, a key component of the Research and Advisory Network.