The modern workspace is flooded with cloud-native apps like Slack, Quip, Confluence, and Jira making it more and more challenging for discovery and legal specialists to keep up, capture, and process data for legal matters. Like rolling stones, emerging apps will continue to grow at lightning speeds.
Onna invited industry leaders from Viacom, Facebook, Caesar’s, and EY to discuss critical topics around e-discovery and information governance related to our new workplace environment. This discussion spanned info gov policies, cost-saving strategies, and machine learning. Popular applications like Slack, Quip, Gmail, and Microsoft Outlook 365 were discussed relating to best practices in capturing and classifying important information.
Here’s a quick look at some of the takeaways from our panel discussion as we consider the future of data discovery and management in the modern workplace.
Better information governance strategies start with knowing what data you have and where that data exists. Having a solution that can centralize data silos, applications, and other tools in one place will help to organize information that is collected and preserved for search later.
Information governance policies provide guide rails, but don’t always prevent employees from acting on their own accord. Rather than trying to enforce them, policy designers should look to evangelize policies based on user behaviors to better align policy to user expectations.
More Accuracy in Machine Learning
Machine learning has hit huge milestones in helping automate the ingestion of volumes and volumes of data for classification. However, the accuracy of that classification has been uneven as algorithms improve and evolve. We hope to see trends that improve user confidence in their search, ultimately becoming recommendations as we see with Amazon, enabling more targeted, relevant information.
The Costs of Inefficiency
It’s safe to assume employees spend 104 hours per year searching for files or replicating existing ones for work, which drills down to roughly 3 minutes per hour of labor wasted on search. If the median US salary is $56K per employee that would average $2,800 in costs per person. For an organization with 10,000 employees the cost of inefficiency could balloon to $28 million lost per year on finding and identifying information. Saving those 3 minutes per hour with optimized search across internal databases is critical for driving down overhead costs.
For an average organization with 10,000 employees, the cost of inefficiency could balloon to $28 million lost per year on finding and identifying information.
Applications rule our daily lives from Slack, Facebook, Gmail, and more. Conversations are ever fluid as employees jump from one platform to the next and continue conversations across applications. Last year, Inc. calculated employees on average spend 1 minute and 15 seconds on a task before getting interrupted. Considering this new behavior in the age of multiple open tabs and screens, providing a single place to focus and find what’s most important is becoming more and more valuable.
Solutions Built For Change
Need and excitement for solutions that can flatten the collection and processing of data into a single platform is growing. The ever expanding set of tools and platforms require a connected ecosystem to cull rising costs of inefficiency and context switching that plague the modern workplace. However, finding a solution with a scalable architecture to collect from cloud-native tools like Slack, Quip, Gmail, and Office 365 for all these use cases is complex.
From Onna’s perspective, we’re building a solution that is future-proof by collecting data directly from API endpoints. An API-based connection methodology bridges the gap between innovative technologies and the need for discovery and data management. As cloud-native apps permeate the workplace, Onna delivers a single solution to capture the needs of large enterprises all the way down to lean startups making information from the most popular applications accessible, useful, and secure.
Need and excitement for solutions that can flatten the collection and processing of data into a single platform is growing
Onna is building a solution that is future-proof by collecting data directly from API endpoints. An API-based connection methodology bridges the gap between innovative technologies and the need for discovery and data management.