CIOReview | | 9 AUGUST 2024second. It is crucial that the BI manager will report (directly or dotted) to the CDO. It was tested in several organizations, and I've never heard of a CDO that wasn't managing the BI Team without a huge struggle thus not being able to bring the necessary value that was expected. By appointing a CDO without the privilege to hold both sides of the equation (creating the data platform and building the analytical layers on top of it) means that practically you're sending a soldier to the field without ammunition. The BI manager will see the CDO as yet another customer (and someone that thinks highly of him/herself) which will politically, for sure, lead the CDO to the bottom of the data food chain.The predictive layer would be accomplished by the CDO only when the data platforms and the advanced analytical skills would reside together under his/her responsibility. In order to push the organization to step forward to the prescriptive layer - he would need strong support from both the business units (at least one VP that will walk the talk with the process) and the IT division.So here is where my story comes into place. You see, being the Chief data officer of a telco company and later on an airline, allowed me to understand the business processes alongside the technical processes behind the numbers. As a data leader, you have the privilege to touch and feel pretty much all the systems that are being reflected in the semantic data layer. The data leader has the unique opportunity to see the full overview and direct link between the business outcome, the technical enablement and the data that reflects all of it.The only thing missing here to complete the prescriptive full potential is to adjust and deploy the insights from the advanced analytical layer (seen here) and the predictive analytical layer back to the operational processes that created the data in the first place. And that is where my role as a CIO comes in place - this allows the organization to become a true data driven company.Let's take a very simple example, that will summarize everything that was written above:As a BI manager for a company that produces air conditioners, you'd be able to gather and organize all of the necessary data and serving it through a BI platform to the analytical units, in order to better understand the behavior of the products in the houses and apartments of its customers. The business will better understand what would cause the problems, what the life cycle of the air conditioners looks like and where are the critical points in which the customer loses his patience. The data can be gathered from the AC themselves (IOT), the CRM systems, the technician report, the weather data, demographic and social information etc.As the Chief Data Officer you'd build the relevant information and data platform, alongside the desired ML models in order to predict the next steps, the outcome of the previous data / touch points, and implement them back to the data products for the relevant alert of the notification / suggestion needed to take place. The CDO would have to engage the VP service and the IT to be able to not only suggest the next step but to implement it back in the operational systems (for example - the technicians task management). The prescriptive cycle would complete only when the business process would change and be adjusted by the insights that would come out of the predictive layer that was built on the diagnostic and descriptive data layers.By allowing the CIO, to have the CDO reporting to him (or in my case, be both), an organization should feel much more comfortable with knowing that the insights would be reflected and implemented back to the technical processes that will engage the desired business process, thus making itself a Data Driven Company. As the Technology Enabler of the Business Desires, being a Data Driven CIO might be the game changer as far as analytics utilization in the operational processes. You see, being the Chief data officer of a telco company and later on an airline, allowed me to understand the business processes alongside the technical processes behind the numbers
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