Back in 1994, I was a fresh young manager at MCI assigned to help the mid-atlantic region better understand and improve performance. Armed with a computer and—for the first time—a direct, non-dialup connection to this new thing called "the internet,” I started thinking... I was seeing all of these web sites (well, a couple dozen at that time) published by companies to display their product information; could we use our nascent intranet to publish our performance data internally?
The answer was "yes, sort of". With Microsoft FrontPage loaded on my speedy Intel 386-based machine, I designed some truly horrific performance dashboards. Black backgrounds, awful logos, lightning bolts—if it was a bad early 90's web cliche, it was on our intranet site. But, the fact was that we had a performance management dashboard complete with statistical process control chart images show performance, patterns, and root causes for our key metrics. As ugly as it was, it was one of the first intranet sites at MCI and certainly the first dashboard of process performance data.
The problem with our setup was twofold: first, we had to collect all of the data manually (it usually took weeks) and second, we had to create all of the analytical elements (charts, tables) as images and then import them into the website. The days of easily accessible data and business intelligence tools were still quite far off. But still, as primitive as our system was, it was a game-changer for performance management and analytics in our organization. For the first time, we could all see our performance in a single, common location.
I remembered this experience when I read an article that asked "are dashboards the next game-changer" and it made me think: are they? Are "dashboards" the next game-changer for businesses?
My opinion is that no, information dashboards in and of themselves are not the next game changer. Which leads to the next logical question — what is the next game changer for performance management analytics? To help see where I believe we need to go, let's take a quick look at where business analytics have been up until this point...
The first wave
The first wave of dashboards was characterized by simply having such a thing as a "dashboard" on the web. Where before executives had relied on MS Excel spreadsheets generated on a daily, weekly, or monthly basis by a team of reporting analysts, those executives could now access that information via a machine interface. I say a "machine" interface, because it wasn't necessarily even a web-based dashboard. Frequently these first wave dashboards were standalone reporting applications that required the executive to login to the app to view the data (or more likely, they had a member of their staff login and print out the report for them to view offline).
A major issue with first wave dashboards was that there was a lack of available, meaningful data. I remember spending countless hours trying to figure out (a) where the information we needed lived and (b) how in the world could we get it out? The horrible, horrible term "screen scraping" was used and used frequently. If you could find the data, if you could get the data out, then you were still faced with getting the data into your dashboard system, creating meaningful analytics, and repeating every week or [cringe] day. These were not the "good old days.” They were the living with old, hard to reach, hard to manipulate data days.
The second wave
The second wave, characterized by data access, made life far easier for most people who worked regularly building dashboards and analytics. Back-office business applications began providing import/export functionality or—better still—APIs that allowed for easy access to the data. Now you could extract data in a real-time or near real-time basis. The era of day or week long information lags was quickly disappearing.
The dashboard in tools themselves also took a huge leap forward. Systems like GoodData, QlikView, Birst and JasperSoft allowed average users to build sophisticated dashboards that could answer many of the questions posed by the business and their analytics could be modified quickly as the business needs evolved. Don’t like the barchart? How about a line chart? Let’s throw a trend line on that. This was an immense leap forward, but was still lacking what management users really required. These dashboards were still very much "read-only" systems—they displayed analytics to the user, but didn't give you any sense of what to do with the data being visualized.
The third wave
And that brings us up to today... These days, getting our information via the internet is second nature. It's a pretty rarely occurrence in 2014 when we can't find the information we need via a quick Google search. We also have (or are getting close to) easy access to performance data—lots and lots of data. These two factors have made the dream of being able to combine disparate data sources into a single, easily-accessible business dashboard a reality. Today we can build dashboards that let us explore KPIs for customer satisfaction, operational efficiency, and sales funnel value all in a single, real-time portal.
And it's mostly useless.
Why? Because we haven't quite crested what I call the "third wave" of analytical dashboards—turning insight into action.
It's amazing that we can now access all of this information in real-time and drill down, drill over, chart, trend, and predict what is going on with our business, but really, this isn't the ultimate goal for analytical tools. The pinnacle of these systems is helping us to answer the question "so what?" This is the third wave.
What we need from the next generation of analytical systems is the ability to do the following:
- show a chart
- find any patterns
- highlight the patterns
- let us annotate the pattern with a root cause
- show u the effective potential solutions for root cause problems
- feed the results of our chosen solution back into the system
- repeat, repeat, repeat
The third wave for business analytics isn't a feature or more data—it's an analytical workflow that takes the knowledge gained from the huge volumes of available data and which helps you determine the most effective solution to improve performance. It’s about turning insights into action.
I predict that future, successful analytical tools will help users to not only visualize the data, but to pick out meaningful patterns (outliers, cycles, etc.). They will allow the user to annotate these patterns with the root causes of the pattern (snow in the mid-west, new employees trained that day, quarter close, etc.). They will present management with possible actions that can be taken when they see such a pattern—actions based on the performance gains that might be expected based on what's observed in the past (in short, the BI system has a memory of what you've tried before). And they will mark the point in time when you implemented a performance fix so that you can correlate the actions taken to future improvement.
The third wave isn't yet here, but it's coming. We've got all the tools at our disposal, the dashboards, the data, the commuting power... Now we need to combine these with the realization that without action, the insight provided by analytical tools isn't much more that eye candy. Let's stop building charts and graphs that look great, but leave us asking "so what?" Let's start building systems that take all the way from "wow—I didn't realize that" to "here's what we're going to do about it." That's the third wave of analytical tools for business. It's about turning insight into action and allowing us to use the data and tools at our disposal to make the most effective decisions possible.