Notes about Cutting-Edge Technologies and Everything

    Central to treating data as an asset, data monetization should align with familiar research and development (R&D) and product management/marketing approaches. Not to oversimplify the many challenges and activities involved in monetizing data, certain basic concepts will reap significant rewards if executed well.  Evolve from Data Project Management to Data Product Management Although you may already have a data leader such as a chief data officer (CDO), or an analytics leader, the first step toward data monetization is to designate a team tasked with identifying and pursuing opportunities for and generating demonstrable economic benefits from available data assets. They may report to a data and analytics executive, into the enterprise architecture group, a chief digital officer, or perhaps even a business unit head.  Creating a distinct, dedicated data product management role is vital especially when business and data leaders agree on pursu...

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The analytics center of excellence has a new mandate for making the entire organization proficient in generating and leveraging automated insights. Data and analytics leaders should include a broad spectrum of organizational, project, data, educational and technological capabilities in their ACE. Key Challenges Data and analytics leaders often struggle to define, establish and communicate the range of analytics capabilities their teams can offer the organization. IT leaders such as CIOs regularly contend that they want to "get out of the report writing business" and expand the notion of analytics from BI application development to enable the entire organization to benefit from data and analytics. Tactical business intelligence competency centers (BICCs), having formed within and emerged from IT organizations, are too limited in scope and technology-focused to provide broad-spectrum analytic enablement. Leading enterprises in most industries generally are more successf...

In a previous blog we discussed how you enable a highly collaborative and data driven organization through the concepts of multi-speed or bi-modal IT.  We then expanded on this through a discussion on the overall information and analytic lifecycle and the interaction with five persona across that lifecycle. You can read those blogs here:  Multi-speed IT drives fast business experiments and empowered citizen analysts Enabling a highly collaborative and data-driven organization Interestingly enough, Forrester Research recently published a report titled “The False Promise of Bimodal IT” which was referenced in an article on CIO.com . Forrester argues this paradigm is fundamentally a mistake as it creates a two class system with the implication that you have a slow moving entity focused on back office systems (IT) with a second group focused on fast roll out of digital products. From an organizational perspective the arguments being made are valid, but when I th...