• Case Study
  • UX

Influencing Factors

Let’s rethink how to integrate information, analyze external data, and…

Let’s rethink how to integrate information, analyze external data, and use the resulting insights to improve decision-making—and transform every planner’s day-in-the-life from good to better. UX can help in addressing issues, improving the data discovery process, and offering recommendations.


Complex pivots and workbenches show data, using real-time analytics we can make these smarter. This real-time visualization can let you see what is happening exactly at all points of the production chain and understand how new factors affect existing data by helping you identify outliers and unexpected outcomes.

Algorithms can assist with getting as granular as needed, running parallel scenarios, and providing recommendations.


Providing the user with smarter insights to enable intelligent business planning.


  • Tools – FigMa, FigJam, GDACS
  • Feb 2021
  • Role – Product Design
  • Tasks- Research, UI, UX Prototyping

What the was situation

Demand workbench showed constraints and even provided shortage. User delight was missing a key add-on – the diagnostic aspect of planning. That includes S&OP, demand planning, dynamic production scheduling, inventory and replenishment, exceptions management…

My solution approach from oops to aha: should include all or a few of the following

  • Descriptive, of what has happened
  • Diagnostic, of why it happened
  • Predictive, of what may happen
  • Prescriptive, of what best can/should be done

What tasks were employed

With focus on Autonomous planning, which enables critical business processes with advanced analytics and artificial intelligence. I suggested 2 ideas: (covering the diagnostic & predictive  approach)

  1. Can we show, what were the influencing factors for the shortage or any KPI measure (confession – not my original idea, but I developed and provided a visual form)
  2. Can some projections be visually shown on the data grid – which helps identifies the chronological occurrence and its magnitude
my aha

Got my Nest thermostat report on usage, which showed me usage and temperature during the cycle. This got me thinking – my usage is a factor of several things geo- temperature, relative humidity, my usage, KWh rate, time of usage, grid load, HVAC unit efficiency, HVAC Filter, and thermostat location.

Learning and being curious – using design to push features and functionality.

What action taken

I created a Figma prototype, showing fake factors affecting a data set, and presented it to the larger team. Data, AI team had a positive response to the approach & direction, where for each shortage they were able to provide data which was aggregated to fewer manageable groups.

Shortage (any KPI measure) now can have a smarter insight on the cause and possible recommendation to resolve the exception (for controllable influencing factors). My original moonshot design provided more data and recommended prescriptive actions, but after a few heated review sessions with UX peers & product dev team.

I scaled down my Figma design with fewer features to get to MVP design into the product. And recorded, good to have features in the enhancement list.

Also created a Figma showing 8 intervals (8 weeks) projection with few visual design options as sparklines and bubble chart in the data grid.

What was outcome

Customer response was overwhelming, much more than expected. Opened the gates for more related ideation and other usages. Like RaaS – Risk as a Service, extend intelligent insight capabilities by ingesting external data feeds, and news, building a comprehensive supply chain risk model, and offer as a service.

What product or processes might be subjected to such risks?
 GDACS – Global Disaster Alert & coordination system  https://gdacs.org/
And so we mostly focus on those first three earthquakes tropical cyclones and floods, as they affect the supply chain more.