Static versus Dynamic Dashboards and Digital Assistants - Who will win in today's contest?


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“By the time you find perfection, your standards for it will have changed.”

If you’re a business intelligence manager or even a software engineering manager, you probably love dashboards for providing a birds-eye view of your most important metrics.
But, are dashboards effective enough? Do you get the actionable insight you need? Or do you have the time to dig for the actionable insight you need? Ohm..right?

Granular details require some time to explore and relevant insights may not be readily apparent. We also feel sometimes that quick answers and actions are just an illusion. But then the emerging trend of digital assistants make us think future is right about to shine.

The performance analytics use case

Improving profitability is of interest to both business intelligence managers and software engineering managers. Let’s take a look at a real use case of how performance analytics works in the engineering world:

An hour of an engineering manager’s time can identify why Samantha consistently has the highest defect rate.

Maybe it’s her code complexity, and you can work out an action plan with her (smaller story point tasks, mentor, code review pairing, walkthroughs).

Cutting her defect rate by just one per month, even if they only take an hour to fix, could equate to an annualized ROI of over 1000% (depending on wage differential).

So, finding ways to help developers to be the best coders they can be is time well-spent. It’s actually an investment.

Data-driven Insights Helps Defining your Investment in the Team

It’s a small step, but it’s an example that you can consistently replicate. This is a better investment then the NYSE or BitCoin! Not to be cold about it, but developer time is a precious commodity. And no one has more of an influence on your team’s performance than BI managers, engineering managers, and analysts.

Data-driven analytics enables you to help the developers on your teams do that 10x thing we talked about earlier. Today’s dynamic dashboards make it exponentially easier to find the specific things that can help each developer code better and improve your entire team’s cycle time.

However, sifting through lots of metrics takes time and doesn’t guarantee actionable insights. And your time doesn’t scale. Or… does it? How many developers or teams are in your organization?

We’ll come back to this after we look at where we’ve been on our information superhighway. We didn’t always have dynamic data, and it can be easy to forget just how easy our jobs are today… compared to chiseling reports on clay tablets.

4,600 Years of Static Data

Clay tablets? Being facetious, sort of. A little bit of fun shouldn’t hurt. Figured a quick look back at the evolution of reports may add some context not just to data, but our exponentially expanding appetite for it. Before we had dashboards, all of the information shared, data recorded, and reports generated for the past 4,600 years were static. It was all… missing links.

Example of an ancient 2600BC Sumerian PowerPoint Presentation
Microsoft Excel 1.5 for Mac (1985) Source:
Gitential’s Dynamic Dashboard for software development performance analytics. 2021 AD

From Static and Dynamic Reporting to Digital Assistants

Static reporting shows everyone the same data for a specific and non-adjustable period. They can’t be changed, without generating a new report – or configuring a new dashboard view. Each user, however, may want to see the information in a different way, or different information altogether. C-Levels and Business Intelligence Managers want to see organization-wide performance just as engineering managers are focused on their teams’ performance. Team leaders want to see how their individual contributors are doing.

Dynamic reporting accomplishes that, streaming or refreshing everyone’s most important metrics so that they’re conveniently available at a glance. Plus, while not a van Gogh, they’re easier on the eye than 1,048,576 rows of an Excel spreadsheet. But, is the data on your dashboard actionable enough? Even if it isn’t, dynamic dashboards provide users the ability to dig into the data to gain deeper insights into what’s going on.

If one hour of analysis can generate a 1000% ROI, how can we further improve the cycle time of the insights generated by our analysis?

Digital Assistants. Dashboards are evolving or perhaps virtually reincarnating as digital assistants. Better than dashboards competing with AI, the two are naturally capable of converging just like the computer converged with telephony and television.

Ray Kurzweil, a director of engineering for Google, cofounder of Singularity, and author of several books including the Spiritual Age of Machines, predicts computers will achieve human-level intelligence by 2029. Most of his predictions have been accurate.

We’re still a few years away, but already AI and machine learning algorithms are much better at pattern recognition than we are. Some smart chatbots can converse on a level that’s nearly indistinguishable from chatting with a human. Functionally, digital assistants are already at a point where you can practically click for insights.

Summarizing Dashboard Capabilities

But, soon 65,000 rows and 255 columns couldn’t feed our voracious appetite for more and more data. And our expectations grew… exponentially. In just over a decade, Excel served up truly super-sized spreadsheets with 1,048,576 rows and 16,384 columns! Our craving for ever-expanding volumes of data is exceeded only by how fast we can get it. Yearly and monthly reports are still useful, but the Internet and streaming technologies make it easy for us to collect and report on data continuously. Some applications, like those used by the New York Stock Exchange, track data by the nanosecond.
  Static Dynamic Digital Assistants
Data and Reports Specific data for a fixed time. Can change context and time frames. Users ask questions and receive easy-to-understand answers with supporting visuals (charts/graphs). “Insights On-Demand”
Dashboards Shows the same data to all users. Each user can customize, interact with, and change their reports as needed.

Transitioning from Dynamic Dashboards to Digital Assistants

Data’s come a long, long way. By the time you find perfection, your standards for it will have changed. Dashboard capabilities are changing even as I write this, but it’s worth comparing the capabilities of what we’ve been using to what digital assistants add for us:


The Typical Dynamic DashboardDigital Assistants 
  • See critical KPI’s at a glance
  • See and rapidly respond to negative trends
  • Measure inefficiency
  • Generate customized reports on the fly
  • Make informed data-driven decisions
  • Align strategies and goals, org-wide
  • Save lots of time compared to running reports
  • 360’ visibility into all levels of activity
  • Rapidly see outliers and identify causes
  • Consolidate reports for “one version of truth”
  • Accessible to “all” electronic devices, anywhere
  • Google-like question-and-answer queries
  • Generate real-time alerts (desktop and mobile)
  • Promote best practices in each scenario
  • Customize data, design, and format of reports
  • Share insights from other users
  • Internal and Industry Benchmarking
  • Responses even non-techs can understand
  • Facilitates “Augmented Teams”
  • Remembers your history (custom FAQs)
  • Easy to see how your data is calculated
  • Makes it easy to add new metrics


10x’ing with Digital Assistants

Business and software development metrics are almost all interconnected in some way. In software development, defect rate is just one of the possible metrics to track for all developers. How many developers are in your team? Maybe you’re managing multiple teams? If so, then you’re also interested in training your team leads.

Remember at the start, we were looking at an engineering case for seeing over 1,000% ROI by spending an hour to help Samantha reduce her defect rate. Her defect rate could be due to her learning a new language, code complexity, maybe poor tests, there could be other reasons, too.

With a digital assistant, the hour an engineering manager spends finding insights for their developers might take 3-5 minutes. Digital assistants also set the basis for augmented teams – and no, we’re not talking about hiring or outsourcing more developers.

A few examples include:

  • Each developer with access to their digital assistant can generate their own insights on how to improve their performance – code review partners and mentors; best practices and advice about who to talk with about how they can improve a specific metric.
  • Team leads and Scrum masters can get insight on optimal story-sizing and not overloading developers showing signs of burnout.
  • Engineering managers can magnify individual efforts by finding challenges common to several developers to arrange for training, code examples, and walkthroughs.

The sum benefit exceeds the value of the individual parts, like compounding interest.

Ultimately, AI-Driven Dashboards – our New Digital Assistants, will provide BI Managers, Engineering Managers, and Analysts with faster insights to help 10x their business and development team’s 10x’ing.

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Don't miss our latest updates. All About Software Engineering Best Practices, Productivity Measurement, Performance Analytics, Software Team Management and more.