AI has enormous promise – driving disruptive innovation in every industry. Leaders will embrace AI and drastically change how they interact with their customers, their suppliers, their employees, and the world around them. We believe that the hardest decision leaders will have to make will be cultural and internal to their organization. Changing what they believe is important for them to accomplish their goals. Leaders will transform sectors to be digitally driven based on a clear view of the business they need to create. Those that try to compete based on old thinking will cease to be viable. For most companies, the challenge will be how not to fall in the middle, trapped between the innovators and the doomed. The risk for these firms is that they will tread water in the short term by applying “digital lipstick.” They will protect existing business lines through cost cutting or tactical automation; they will pay lip service to new business models while preserving legacy tactics, burying their head in the sand, trying to hide from this disruption. Most telling of those in the middle will be their fear of breaking internal center of power or silos. They will fail to lay down a digital vision for their business, instead trying to compete based on analog foundations in a digital world.
AI-driven digital will yield competitive advantage, improve customer experience, and reduce cost through strategic automation. However, despite the promise of AI, most enterprises will struggle to succeed with AI. One of the greatest challenges in becoming a digital enterprise is that data in “analog organizations” is siloed across hundreds of systems – each representing a semi-autonomous non-collaborating business or technical silo of the organization – with conflicting views on what the business reality is. This data resides in ERP systems, data warehouses, data marts, data lakes, databases, and file systems that are not connected, not to mention AI-enabled. The problem for companies is that they waste significant energy and time combining, enriching, cleaning, verifying, and organizing the data to get it ready for modeling rather than doing the modeling itself. Analog organizations will spend more time rationalizing conflicting views of the business than delivering business value.
Unite your data with AI to transform your business and revolutionize your industry instead.
Unified analytics within the modern digital estate for AI
Siloed units within organizations are not going to disappear. However, with separation of storage and compute, it is now possible to have a single repository of organizational knowledge that is distilled/acted upon to serve a specific business unit or purpose without affecting another. This new standard allows AI to run with greater fidelity and accuracy and it drastically lowers the cost of data management while allowing for significant acceleration in delivering AI outcomes.
Unified analytics (UA) makes it easier for enterprises to build data pipelines to connect the complex siloed data networks that exist in most organizations and label datasets for data science, allowing for centers of gravity of data to solve multiple business problems for multiple organizations without spending energies rationalizing these perspectives.
UA also provides access to a broad set of AI algorithms that previously existed within organizational silos, never to be shared. UA is an easy way for a digital organization to light up AI for the various stakeholders, allowing them to collaborate on data and algorithms without having to resort to “old-fashioned-governance.” In fact, UA allows governance without requiring fundamental, hard-to-implement changes to an organizations culture. It combines the power of cross-domain data with white gloved service tailored to each unit.
“The power of unified analytics cannot be overstated.
