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Data, AI and automation:
An Rx for your modern workforce

Learn how to leverage modern technologies for predictive insights and cutting-edge action

Dec. 4, 2020 | By: Kris Mercer and Ramesh Vishwanathan

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Forward-thinking, innovation-enabling technologies like AI and automation are all the rage for modern workplaces. Organizations are trailblazing into the new—excited to prioritize the end user, strengthen their internal core, and optimize mobility and self-help enablement. The problem? While many of these technologies enable a progressive approach using data insights and predictive analytics, businesses are still very much stuck in a rear-view perspective, unable to find actual value in their data to make proactive and innovative strategic business decisions based on trends. Although an irritating workforce ailment, it’s very common and, very treatable.

The symptoms: Signs it’s time to consider automation

Increase in cost per user, low incident resolution, subpar customer satisfaction, slow troubleshooting. Does this sound all too familiar? Modern enterprises that are behind on being data-driven often get hung up on solving for these symptoms without recognizing the leading indicator of their problems. Companies typically experience issues that they never seem able to find the root cause of. For example, you may not be aware that your end user is signing in and out of your app on multiple devices because your data only tells you that you’re getting a mass number of password resets per month—you’ll never realize the solution is to change your process to include single sign-on for users. Merely collecting data isn’t enough—breaking it down and turning analytics into insights is where you’ll start connecting the dots.

The diagnoses: No clear data strategy

No data-driven culture: Organizations have always seen their data as an asset, and in the last five years, more and more have realized that data can be used as a competitive advantage. But the missing piece of the puzzle is understanding what type of data is needed for you to truly be data-driven, drive change and act with agility—how to collect it, process it and leverage it for competitive advantage.

Lack of data strategy: The key to a strong data strategy  is establishing a long-term business vision and then driving the strategy toward it. But constantly evolving market conditions and business models force us to consistently relook at our data strategies to address current impacts and future plans. Every organization should reevaluate their data strategy and realign themselves based on how the business performs outside of external influences.

No automation and dashboarding: The value of data is only realized through properly finding root-cause analysis—assessing its value, identifying problems, and finding patterns and relationships. Automation technology can help reduce time and increase operational efficiencies needed to predict outcomes and prescribe solutions. Automation can be leveraged to analyze large volumes or wide varieties of data and should be represented in digestible formats and dashboards that can be easily interpreted and shared when processed through analytics platforms such as Tableau.

The cure: Put your data to work

Find areas of your business that you can automate: The benefits of automation are unrivaled—from new ways of working to putting data to work. Plus, when companies need to respond to disruption, those that will be successful will respond quickly based on their data, numbers and feedback—in real time. To use data critically to influence agility and make sound business decisions, organizations must cultivate a data-driven culture through technology and people.

Add value to your data: By integrating automation, you'll enable your data strategy to offer predictive analytic insights into trends and relationships, as well as prescriptive recommendations on how to take action toward organizational goals, future modernizing your workforce. Given the right set of data, AI-driven operations enable organizations to move toward proactive management at speed from a traditionally reactive approach. You'll be able to dig deeper using predictive modeling and generate automated alerts—learn, adapt and improve.

Clean up your data: Any autonomous engine is only as good as the quality and rigor of training it was provided. Inherited data issues will invalidate the process and potentially have negative impacts on business value. To power business decisions with predictive analytics, processing and creating a meaningful and clear data strategy to clean up your data will make all the difference.

A roadmap to recovery

Modernizing your enterprise comes down to the ability to respond, make intelligent timely decisions and ultimately predict. Automating business processes and augmented intelligence should be used to fuel those actionable insights—ultimately achieving growth, generating monetization and curing that workforce ailment.