Aperio AI

An excellent report by Capgemini on the growth trajectory of smart factories. It was put together by surveying 1,000 executives in organizations that had a smart factory initiative underway.
Get the report here: https://lnkd.in/epFyrAMt

Came across this blog by Ataccama showing the impact of data quality automation on data scientists' time. Not disputing what's depicted, but I'd argue that APERIO could further drive the time spent Preparing Data from 20% to zero.

An excellent summary by Jay Agrawal, Sean Buckley, CFA and others from McKinsey & Company on how adoption of AI can greatly improve industrial output and efficiency. The article describes the exact same problems APERIO DataWise™ is tackling:

https://lnkd.in/ezTpE9n

APERIO is at Globuc's Go Digital Event in Amsterdam where they're talking about . Cognite estimates the loss of revenue due to poor data quality at 30%. This is in line with what we're seeing our customers experience. https://lnkd.in/geWtTEcf.

APERIO are thrilled to be exhibiting at Globuc's 6th Annual Go Digital Energy Conference on the 7-8 June in Amsterdam.

We will be exhibiting in Booth 12 and speaking to companies from the whole energy value chain about APERIO’s revolutionary AI approach to minimizing unscheduled downtime and increasing operational efficiency. We hope to see you there!

Register here: https://bit.ly/3x7BQJk

Our latest success story demonstrates how APERIO DataWise™ is solving data quality issues across a wide range of industrial sectors.

In this example, APERIO is enabling true predictive maintenance at a multinational mining company.

Read the success story here: https://bit.ly/38OGAMb

Don't forget to catch APERIO's CEO Jonas Hellgren and International Paper’s Manufacturing Process Information Manager, Rick Smith at the Connected Plant Conference on Monday 23 May.

They will be presenting on how manufacturers can leverage to drive performance improvements and asset health and reliability.

Let us know in the comments if you want a copy of their presentation or register for the event here: https://bit.ly/3lsHkZM

APERIO is proud to present at the 6th Annual Connected Plant Conference on the topic of "Democratizing Your Data". We will be speaking alongside International Paper - an APERIO customer and the biggest paper and pulp manufacturer in the world.

The event will also feature other leaders in the digital transformation space. These include AVEVA, Amazon Web Services (AWS), Delek US Holdings, Inc., Covestro, Stanley Black & Decker, Inc. and others. Read more about our plans for the event here: https://bit.ly/3sy49ze

We asked 160 professionals how they currently handle operational data quality issues. A majority clean data manually or use rules-based technology. Are we not tired of these labor-intensive time wasters and ready for a tool that automates data integrity across the enterprise?

In our latest customer success story, APERIO DataWise™ helps a global chemicals and minerals company consistently avoid equipment failure and unscheduled downtime. Read the full story here: https://bit.ly/39omjwN

People’s experience and/or process performance (KPIs) are commonly used to “measure” the quality of data. Only 6% use a tool to measure data quality and only 4% track data over time. How precise is your data quality measurement?

This article by Joe McKendrick of RTInsights and Jay Agarwal , former consultant at McKinsey & Company touches on many issues that APERIO is tackling through its data quality platform: "6 Rules for Energizing the Data Behind Industrial AI": https://bit.ly/3EDipeN

We asked 160 professionals to grade the data quality/integrity of their operational data presently. Only 4% say data is always clean, accurate, and accurate while 44% say it’s clean but can’t say how they know. Sound familiar??

AI is gaining momentum in industry 4.0! An interesting article by Bill Scudder of Aspen Technology and RTInsights: "4 Ways Industrial AI Will Reshape Manufacturing in 2022": https://www.rtinsights.com/4-ways-industrial-ai-will-reshape-manufacturing-in-2022/

When asking decision-makers (split is 91 IT/64 Ops) who bears responsibility for solving quality issues in operational data, half believe IT does. This number rises to 67% when strictly asking IT surveyees. Do you agree?

An interesting report by HFS Research on how "Bad Data Kills Data Transformation Efforts".

Link to the report here: https://bit.ly/3J7qRE0.

Solving data integrity issues has been a 30-year struggle. We asked 160 professionals, what is preventing you from solving operational data integrity issues? RESOURCES—as in, people, cost, time—was the top challenge! Do you agree?

We asked 160 executives to estimate how much revenue is lost due to poor operational data quality. The average was 5.6% when in reality it is closer to 15%. Are you underestimating how many $$$ you are losing because of poor data integrity? https://aperio.ai/ebook/.

We asked 160 professionals, where does inaccurate, unreliable operational data have the greatest impact? 60% said poor data quality has a direct impact on plant performance through operator error or unscheduled downtime. Do you agree?
Learn more: http://aperio.ai/ebook.

Industrial Data Analytics Pioneer Jon Peterson Joins APERIO as Chief Product Officer https://lnkd.in/eAd_U8Rv

Industrial Data Analytics Pioneer Jon Peterson Joins APERIO as Chief Product Officer /PRNewswire/ -- Jon Peterson, a leading authority on industrial data analytics, has joined APERIO as Chief Product Officer. A 30-year veteran of the industrial...

Are the Olympics about sport or data? Why it's time to look at your data with the same scrutiny as an Olympic athlete!
https://lnkd.in/eeXR7BUQ

Are the Olympics about sport or data? - APERIO Because every element of an Olympic athlete is optimized, micro insights are invaluable. It's time to look at your data with the same scrutiny!

The World Economic Forum recently published a paper called “The Data-Driven Journey Towards Manufacturing Excellence”. It explains how the quality of actionable insights, predicting future outcomes, or enabling self-optimizing systems, is strongly dependent on the quality/integrity of the data. It explains how AI machine learning, like APERIO’s DataWise, is necessary to achieve all three.
https://lnkd.in/e3XqeiKb

The Data-Driven Journey Towards Manufacturing Excellence This white paper sheds light on best practices and real-life use cases implemented by the leading manufacturers that co-developed and applied the framework across their facilities.

"Data integrity has become the #1 inhibitor to maximizing ROI in digital solutions, with more than 50% of today’s data science budgets dedicated to cleaning data.” Learn how to fix this: https://lnkd.in/d9Nskg_w,

The Costs of Poor Data Quality in Industry - APERIO APERIO CEO Jonas Hellgren explains the true cost of poor OT data integrity in operator decision making and asset health and reliability.

OT data is growing exponentially but much of it is underused or untrustworthy. It's estimated that poor data quality is costing industrial companies up to 15% of revenue. Download our data quality E-book and learn how you can improve your data quality and make data cleaning a thing of the past: https://aperio.ai/ebook/