Announcing TrustPlace Advanced Analytics

Brian Carpizo

November 23, 2021

Powerful & Configurable Insights for Operations

Harvest the "Digital Dividend" With TrustPlace's No-Code Platform

Digitizing workflows in built world operations at the unit level has many advantages – consistency, quality, and efficiency. But the real “digital dividend” for organizations is when the digitized work data is available for insightful analysis. Companies want to be more data-driven in their decision making, but the cost and complexity of traditional Business Intelligence (BI) solutions prohibit most companies from putting their data to work in a meaningful way.

To capture this digital dividend in a simple, affordable way, today we’re announcing the beta availability of TrustPlace Advanced Analytics to provide this powerful capability for our customers. 

About TrustPlace Advanced Analytics

Built on top of TrustPlace’s no-code platform,  TrustPlace Advanced Analytics provides operations leaders with a highly configurable set of multi-dimensional data analysis views – including KPIs, visualizations, and machine learning-derived insights.

Going far beyond traditional financial metrics, operations advanced analytics helps companies back up high-velocity decisions with lighting-fast insights aggregated from the “ground truth” across the footprint of the entire operation.

The TrustPlace advantage in the marketplace is derived from our no-code building blocks – our organizational structure, one workflow + data collection data set, including IoT sensor data. This simplicity belies the power and virtually unlimited set of insights we can produce for operations leaders.

TrustPlace Advanced Analytics Features
  • In-memory calculation engine that achieves blazing fast performance at scale
  • Flexible aggregation schemes on dimensions (locations, departments), measures, and dates (hour, day, month, quarter, year)
  • Dozens of visualization types (waterfall, tree maps, heat maps, geospatial, bar/line/pie charts)
  • Dozens of analysis types (pivot tables, changes over time, correlation/distribution)
  • An unlimited set of derived metrics (calculations) – ratios, differences, combinations (think: baseball advanced statistics)
  • Machine learning powered analysis (anomaly detection, forecasting, natural language narratives)
Corrective Action Analysis Driven From TrustPlace Workflow Data

Monitor KPIs and Derive Insight

Zoom Out: How Are We Doing?

At the highest level, aggregate measures provide top level leaders with metrics used to evaluate operational performance. 

These can be evaluated against goals and benchmarks to quickly ascertain where things are going right – or wrong.

Trends against time also helps to contextualize the story, as well as location dimensions for built-world operators with multiple locations.

Lists of “top X things” happening provide an at-a-glance glimpse of what is going on in the weeds.

Machine learning derived insights can automatically identify things like anomaly conditions, or forecast where things are likely to be in the future.

KPIs with Targets

Dimensionalize, Drill Down & Drive Decisions

Zoom In: Where Should I Take Action?

Drilling down from the top level helps fill out the story, especially when a leader is seeking to understand exceptions (positive or negative).

Dimensions on the data (time, location, geography, people, teams) help pinpoint where there are opportunities for action or follow-up.

And conditional formatting (think: green light, red light, yellow light) helps identify where in the detail an operations leader should take notice.

IoT Data Analytics With Machine Learning Insights

Built on top of TrustPlace’s IoT module,  TrustPlace Advanced Analytics identifies trend and insights from time series IoT sensor data. Example sensors we see useful in built-world operations:

  • Temperature
  • Humidity
  • Air Quality
  • Motion / Occupancy Detectors
  • Water / Water Levels
  • Current / Voltage
TrustPlace Advance Analytics can identify trends and outliers in IoT sensor data, providing insight into built-world conditions. Machine learning powered anomaly detection can continuously analyze sensor data to discover anomalies and variations inside of the aggregates, giving operations leaders the insights to act when business changes occur.

Capture & Analyze Data Gaps With TrustPlace Workflow

One of the pain points for built-world operators seeking to become more data-driven in their management and decision is access to data. Two problems exists:

  1. Where there is data for analysis, it is most often collected manually and displayed in spreadsheets or in presentations. This is time-consuming and error-prone.
  2. Where there is no data (gaps), operations managers are left to hypothesize the “why”, often cherry-picking a few anecdotes or relying on the stories of potentially unreliable narrators.

TrustPlace’s Worfklow + Data Collection solves this problem by providing an automated mechanism for collecting ground level truth from operations – so it can be useful in the form of data analytics.

An example: the restaurant manager’s daily “Redbook” is usually a manual (paper or spreadsheet) that logs daily operations results and conditions. Digitizing this into data analytics across hundreds of locations provides leaders a powerful way to identify operations drivers for success.

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