Why incomplete data can be as dangerous as bad data
May 18, 2023
When it comes to data in general, and AI specifically, a refrain you’ll hear constantly is “garbage in, garbage out.” The point is not to critique any organization, but to warn that without a proper foundation of good data, the resulting strategies will always fail.
Most leaders understand what bad data is. Data entered manually, for example, is much more likely to be incorrect than data pulled automatically. Similarly, reports built from data combined across multiple platforms can result in duplicate data, which can negatively impact projections and strategies.
But bad data isn’t just inaccurate. Incomplete data can be just as dangerous to your workflows, strategies, and productivity. Until recently, companies assumed that a complete view into their workflows was impossible. Some work simply couldn’t be measured. But it simply isn’t true. In fact, in today’s world, with demands from customers and stakeholders as high as they are for everyone, comprehensive data is a necessity.
Understanding all work makes productivity possible
Enterprise organizations leverage a suite of tools to execute their various workflows. Some estimates say that the average worker can use about 10 apps in their daily work. A single department can have between 40 and 60 applications, and the average company has over 250.
Alone, that creates a lot of data to collect, organize, and ensure the accuracy of. Companies must also consider that many customer-facing teams, including sales and customer success teams, don’t believe they are using their technology to the fullest potential. That means much of the work teams complete each day goes unaccounted for in the data.
The disconnect between what employees do every day and what the data shows can impact everything from your company culture to the efficiency of your revenue strategies. Pushing your employees to do more without a complete view into their tasks and workflows can breed resentments and burnout, which negatively impacts productivity and longevity. What’s more, when you build a workflow based on incomplete data, you are building in unrealistic expectations for timelines, headcount, and ROI.
Put simply, you set yourself up for failure with incomplete data.
The customer experience happens everywhere
Incomplete data affects more than internal teams or workflow efficiency. Customers are on high alert for personalized engagements that deliver value from your team. Any conversation in which they need to reiterate their goals, obstacles, or needs creates a negative experience for them. A poor impression from customers, particularly in today’s market when competition is at an all time high, can lead to churn.
A majority of today’s work happens in the browser. Employees connect with customers through chats and on third-party sites, like LinkedIn. Meetings often cover topics outside of what’s detailed on the agenda, and unplanned demos of product features can happen for sales teams. If these details aren’t included in your workflow data, your operations teams may suggest a next best action that is redundant or irrelevant for your customers. You risk looking unorganized to customers, plus they may start to wonder if your team values their business.
The simplest way to avoid both of these issues is to leverage a workflow intelligence tool that gathers data from across all your workplace applications to give you a comprehensive, detailed view of all your efforts.
Complete your data and increase productivity with Retain.ai
To see how a complete view of your workflow data can improve your operations, increase productivity, and create a better customer experience, schedule a demo with us today. In as little as two weeks, you can start collecting data from over 500 applications right from your browser. The gold-standard for data is possible with Retain.ai.