Not surprisingly, there is no single approach to embracing data-driven innovations within any industry vertical. However, there are some enterprises that are doing a better job than others when it comes to establishing a culture, process and infrastructure that lends itself to data-driven innovations. In this talk, we will share some key foundational ingredients that span multiple industries.
Abstract: Every single public company is under pressure from the Board, CEO and senior leadership to become more data-driven and agile. This inevitably leads to “answers” such as Cloud, Analytics, Machine Learning/AI and the corresponding adoption of tools in that space. Some of these initiatives are more successful than others – where success is measured by business impact within a certain reasonable time horizon. We have observed that the greatest success is achieved in organizations that not only start with end in mind but remain true to it every step along the journey. For example, companies that want to fundamentally change how drug discovery is being approached need to start with a blueprint for a new R&D strategy before procuring tools. Similarly, companies that want to embrace advanced ML/AI need to ensure that the right data sets are available for use. Equally important is organization structure, skillset, and reporting structure that can aid or hinder innovation. We, at Cloudera, have had the benefit of working with customers that span a variety of industry verticals spanning healthcare, banking and financial services, governments, retail, manufacturing, autonomous driving companies to name a few. In this talk, we want to share the learnings of how some very successful organizations have adapted their culture, process and infrastructure to herald a new age of data-driven innovations.
1. Importance of having long-term business goals that drive data-driven innovations. Without this, it is easy to get lost in endless explorations.
2. Baselining whether the existing culture is the right one for executing on the vision and if it is not right, coming up with a plan to change it.
3. Making sure that the innovation process and infrastructure choices are in alignment with budgetary expectations, business realities and the cultural mindset.