By Atashi Bhattacherjee
Throughout the many years of helping companies create and implement their reporting strategy, we have brainstormed and worked through various external factors that could affect an analytics roadmap so that we could adjust it appropriately to accommodate for theoretical events. Still, we never fathomed the potential impact of a global health crisis like Covid-19 would have on a company’s reporting strategy. The advent of a global pandemic has proven to all of us, that no matter how robust a company’s reporting strategy and despite the most current advanced technology, the most essential component in times like these is the reporting strategy’s flexibility to change – How quickly can you make the data available for decision making? That flexibility is embedded in your Analytics team’s operating model and ability to intelligently navigate through a rerouted roadmap.
How quickly can you make the data available for decision making?
Many companies at this time are not utilizing all the analytics solutions that they have built over the years. Despite their previous success, the company needs have shifted to a more frequent reporting model requiring a nimble approach. Two problems that business analytics teams are currently facing are rooted in the reporting strategy. First, organizations have found that their reporting models can only highlight metric changes over a certain defined time period, for example, monthly, quarterly, or simply no changes at all. This logic has been embedded in the reporting model which means it cannot be changed as needed. This model does not help during times when there is a business need to see the data changes on a more frequent basis. Second, business stakeholders are finding that their analytics are not displaying all the metrics they need to see in one place. The first usually happens because the complicated nature of storing daily variations in data proves to be costly and it is difficult to justify such investments. In a stable environment, there is little ROI for that type of storage capacity. The second challenge is what I call “Analytics Addiction”. This is when we are building dashboards indiscriminately without thinking about how it feeds into an organization’s overall reporting strategy as well as cross functional needs. Organizations are now creating analytics specifically designed to solve the problems that a global crisis has brought to the surface for them. The speed with which these analytics are produced is of the upmost importance because swift decision making is essential in today’s climate. As a result, in some of these cases organizations are looking beyond the technologies that they have used in the pre Covid-19 world and are now urging their Analytics team to use any skill and technology that speeds the process of creating such analytics. This is where the strength of your Analytics Operating model is put to test. Organizations need to examine if they can pull in the right people, the right skill set, and the right technology at that time for that particular business problem to help the business make critical decisions.
Adaptive Reporting Strategy
Let’s take a closer look at how we strategize a reporting model. When we design an analytics application and build metrics for a group of stakeholders’, key questions we ask are;
The answer to these questions determines the architecture that we are going to deploy behind the scenes. Often, the answer is a balancing act driven by the cost of storing that size of data. However, that architecture is reactive and caters to the immediate business problem at the time of development without keeping in mind that the frequency of viewing or comparing the metrics may change in future. In an ideal world the answer would be – “Why don’t you allow me to see the changes in metrics at any and all frequencies or, on-demand”. A flexible frequency rate for reporting is certainly an ideal reporting strategy. However, using current technology while keeping the cost justified will reside within the strength and adaptability of your Analytics Center of Excellence. These are the people who can move across technologies when needed by leveraging different skill sets with solid business understanding to create analytics that drive decisions while keeping the importance of speed and time in mind. Organizations must invest in technology as well as a strong Analytics Center of Excellence in order to get the most value out of their Analytics.
Analytics works best when it does not have technical guardrails around it. Creating a robust team will give the required flexibility to an organization’s reporting strategy. A continuous effort of re-defining the analytics teams operating model will ensure that the Analytics CoE can monitor rapidly advancing technologies and business challenges to adjust as needed.
Atashi leads the Analytics and Business Operations capabilities at MResult. With over a decade worth of Banking, Specialized Research and Analytics experience Atashi and her Analytics CoE Team are responsible for managing projects for organizations of all sizes including large enterprise clients. Leveraging the team’s analytics expertise to solve critical business hindrances have afforded Fortune 500 and mid to small sized companies alike, the ability to streamline their business processes and enable data-driven decision making.