The Dashboard Is Dead

How Decision Intelligence can save thousands of hours and give organizations anywhere a competitive advantage

The problem businesses worldwide face is that they’re slow at making decisions.

The scale and growth of data is so great that humans are unable to understand the complex interactions inherent within that data. To help humans make the right call when faced with a complex decision, they require relevant, pertinent facts to make the best decision possible. In the industry, relevant, pertinent facts and information are referred to as “insights”. However, the analytical tool ecosystem is fragmented and inefficient — making the process of finding insights inherently slow.

The most common solution is the dashboard — a collection of visualizations. While they’re the most common, they suck as a standalone tool. Yet this is what many companies provide to help solve complex problems.

Typical insights process

The typical analyst spends hundreds of hours per year manually slicing, dicing, crunching, cajoling, coaxing, tempting and luring real insights from their data. This is causing businesses to move slowly, losing out on the big things — new opportunities, first-mover advantages, business models — as well as the small things, such as shifting their marketing mix, responding to customers in a timely manner or training employees in a new skill.


My preferred robot interaction

When you think of automation, you might think about a gargantuan robot moving huge pieces of metal in a factory of the future. Others imagine artificial intelligence systems as whirring and buzzing black boxes, spitting out a magical output that totally replaces a human. This dystopian view of the future is popular in science fiction, bu far from the truth.

The true future of artificial intelligence is human driven, with these technologies supporting humans across every industry. Artificial intelligence tools unlocks the power of human capital, making humans assisted by artificial intelligence tools 30% more productive than their peers. When applied specifically to data analysis and supporting complex decisions, artificial intelligence tools make a stunning difference.


Quantifying the impact of AI tools on analytics

Let’s take an average organization. There are at least 5,000 companies in the US over $100M in annual revenue today (assuming the number of companies have not decreased in recent years). Let’s use a $500M company as a safe benchmark. If we assume $500k revenue/employee, we’re looking at 1,000 employees. If just 5% of those are individuals that work with data to support critical decisions (50 people), and they spend just 5 hours per week on working with data manually, that ends up being 250 hours/week and 13,000 hours/year spent on manual analysis.

If AI-based decision intelligence tools can reduce that time by just 20%, that would be 2,600 hours per year saved across this organization. This is more than one person-year in time savings (over $100k in direct time savings if these employees make $80k/year).

This company would move faster, make better decisions, further growing revenue, reducing unnecessary losses and improving their strategic footing. All with happier, more effective employees who are working on higher value tasks — not on manual data preparation, analysis and summarization.


Every organization is different in their size and scale. All organizations share one common thread: they could be better at making decisions. No matter how streamlined your processes or talented your people, your data can help you be better — but you likely aren’t using AI to make those decisions at the speed of thought.

To see how much time your organization is wasting on manual data analysis in support of critical decisions, check out the simple calculator below.

Businesses of every size, industry and age can benefit from automating manual analysis at scale in order to move faster and with more focus. If you want to make better decisions about your data, try us out @ www.tellius.com/free-trial.

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