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In my perspective on decision intelligence, I lamented the fact that business intelligence technologies have left the rest of the exercise to the reader for too long. Making a decision is a process that involves many steps and many people. Decision-making is so complicated and divorced from day-to-day business processes that organizations have had to create entirely separate teams to focus on the analytics and data to support it. One aspect of the decision-making process that can be enhanced by technology is collaboration.
Rarely are decisions evaluated, made and implemented by a single individual. This is true regardless of whether the analytics to support the decision are done by a separate team. Data needs to be collected and analyzed to determine what happened. Alternative responses or scenarios must be developed and evaluated to determine the best course of action. Typically, some debate takes place since the decision(s) will impact multiple parts of the organization. In addition, there is uncertainty and risk involved in the various scenarios, so additional subjective input must be considered. Ultimately, a person or group authorized to make the decision determines which course of action to implement.
But the process doesn’t stop there. Once the decision is made, it must be communicated to those involved in implementing the response. A disciplined and well-governed organization would want to monitor the implementation to ensure the plan has been carried out as instructed. That same organization would want to document the entire process from end to end both for compliance purposes and to share the knowledge of the decision-making process with others. Organizations recognize the importance of collaboration software in analytics processes. Two-thirds (68%) consider it important or very important. So, why not use technology to help support the collaboration involved in decision-making? There are many technologies available that benefit these processes.
Organizations should consider the following types of capabilities for collaborative decision-making:
Most analytics tools make it relatively easy to share analyses with others. Typically, this involves granting permissions to different users or roles. Often, analyses can be shared other ways as well, such as emailing an analysis or sharing a URL that links to the analysis. Unfortunately, too many products stop there. Going beyond those basic capabilities, it is helpful when individuals can attach comments to the analyses and mark up the analyses with annotations directly on the screen. Ideally, those comments are searchable in the catalog of analytic objects. The comments may also be restricted in some cases to certain individuals, just like other elements of data. It’s also helpful when individuals can like or endorse analyses, helping to identify which analyses may be most valuable.
Threaded discussion groups, wall posting and broadcast messaging were popularized by social media platforms. These techniques facilitate dialog and knowledge-sharing with stakeholders. Not only do messages get information to the people involved in decision-making, but they also form a body of knowledge that can be searched by others in similar situations. All of these capabilities are valuable in analytics processes.
But merely communicating about decisions is insufficient. Organizations should support and manage the workflows around analytics processes as well. Workflow management and automation tools help ensure the proper actions are taken both during and after the decision-making process. If a decision is needed, workflow management can be used to route the information to decision-makers and track the status of their review process. At any point in time, the status of the decision-making process is known and, if necessary, a task can be delegated or escalated to move it to completion.
Tracking the discussions and workflows associated with analytics also provides a foundation for good governance. Decision-making processes can be documented for compliance purposes and reviewed for both effectiveness and efficiency. In an ideal world, even the training of individuals on the use of technologies involved in the process could be tracked – and some tools do this already.
Organizations should have higher expectations than merely sharing analytic objects and documents. Analytics and BI vendors are adding collaboration capabilities to products and integrating with external collaboration platforms. In fact, we assert that by 2025, 8 in 10 BI software platforms will include collaborative capabilities designed to support organizations’ decision-making, task management and compliance requirements associated analytics . Putting these collaboration capabilities in place helps facilitate better decision-making and more efficient decision-making processes.
Regards,
David Menninger
David Menninger leads technology software research and advisory for Ventana Research, now part of ISG. Building on over three decades of enterprise software leadership experience, he guides the team responsible for a wide range of technology-focused data and analytics topics, including AI for IT and AI-infused software.
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