The role of analytics on the journey to the cognitive enterprise (Part 2 of 2)
By Carol Zichi | 2 minute read | April 3, 2019
Traditionally, disruption is the last word IT wants to associate with.
But demand for more intuitive, intelligent user experiences in the workplace, along with the proliferation of devices and data, challenges long-established notions.
CIOs aspiring to a cognitive enterprise model must bring automation, analytics and AI to the workforce. Cognitive capabilities replace the act of giving workers access (to systems, apps, tools and so on) with the power to enable them through self-healing, predictive action that continuously optimizes the worker experience. (See Part 1 of this blog.)
IT bears the weight of ensuring the enterprise adapts to these new ways of working, without impacting performance, security, compliance, profits or costs.
In other words, to achieve a cognitive enterprise model, IT must become a disruptor and change agent.
IT must also get comfortable with cognitive analytics.
How the cognitive enterprise impacts IT
- Success will be measured based on IT’s impact to the business versus traditional service level agreements or key performance indicators.
- Anytime, anywhere access for workers will be a given. IT will use cognitive and AI to assist workers with routine tasks so they can focus on higher-value activities.
- IoT will be integrated into corporate systems versus just being part of the corporate infrastructure.
- Support will evolve. Self-healing and predictive actions will continuously optimize user experiences.
To keep up with the rapid pace of change, and enable workers in the cognitive enterprise, IT has to work and think differently.
Cognitive analytics is IT’s greatest asset
Enabling workers with the cognitive experience requires a deep understanding of current user experiences and a strategic vision for the ideal, modern user experience. Data thus becomes the most important asset.
7.5 quintillion bytes of data are produced daily1 — data from devices, systems, applications, channels, and other sources. With 75 billion connected devices expected by 2025, the data volume will continue to surge. The potential within that data for workforce optimization is limitless. But traditional analytics solutions can’t handle the enormous volume.
Delivering the cognitive enterprise requires a cognitive approach. Cognitive analytics enables IT to turn vast amounts of data about workplace processes and worker experiences into actionable information. It can identify productivity blockers and understand why they are occurring. Armed with this insight, IT can automate associated processes to fix the issues and optimize experiences.
What my clients say
The CXOs I know who are using cognitive analytics say they now can make more informed decisions. They are boosting worker productivity, efficiency and satisfaction, while also optimizing costs.
They say the predictive and proactive approach to maintenance and support —made possible by cognitive analytics — enables their IT managers to resolve more issues before they impact users.
They also say ensuring compliance and managing change is now faster and easier, despite the constant introduction of new services, devices, workers and processes.
Take the first step towards the cognitive experience
A dynamic and continuously optimized workplace is an incredibly exciting vision.
In a cognitive enterprise, machines cover the burden of tactical, routine and administrative work. Teams then can focus on what makes them uniquely and powerfully human — the abilities to collaborate, imagine possibilities, and innovate in ways that create value for the world.
Cognitive analytics is the first step.