1 Oct
2019

Big Data and Budgeting

In this article we’re going to dip our toes into the near future of manufacturing business and discuss Big Data and Budgeting.

Big Data
Big Data and Budgeting

In other articles we discuss the many advantages of IIoT technologies and the power unleashed by having a Smart Factory Analytics dashboard at your fingertips. In this article we’re going to look more broadly and dip our toes into the near future of manufacturing business and technology. Having the ability to see in real time what’s happening across your production environment enables you to engage people and apply processes to continuously improve your manufacturing performance. However, as manufacturers accumulate data, it’s inevitable that they’ll want to find more and more ways to monetize this information.

One area explored by Thomas Insights is the application of Machine Learning to IIoT data. In their article Big Data, Better Budgeting: Machine Learning for Facilities Management they explain how not only will IIoT data be used to respond to manufacturing information such as upset conditions, but that, as enough data gets collected, Machine Learning will be able to be applied to make predictions. “By establishing operational patterns, it’s easy for facilities managers to develop proactive system scheduling: parts ordering, cleaning, routine shutdowns, and equipment replacement can all be arranged at the most cost-effective and efficient times.” It only makes sense that once you can make accurate predictions of production upset possibilities or machinery maintenance downtimes that you’ll be able to budget more effectively.

However, thinking even bigger, as we noted in our article Industry 4.0 and Efficiency - A Global Perspective, there is a new role emerging in manufacturing, the CSCO, or Chief Supply Chain Officer. The adoption of this role is accelerating because as companies get their internal Industry 4.0 initiatives in place, a natural next step is to connect to other key stakeholders in their value chain in order to share real time production analytics. This daisy chain of data, from raw material to finished goods promises to remove waste from the supply chain entirely.

This also holds another promise however. Having real time insights into demand while getting actionable supply data, also in real time, manufacturing businesses will gain unprecedented visibility into their own future.

In the not too distant future, financial analysts at manufacturing businesses will be able to see actual production metrics as they’re occurring. While operations managers will be focused on streamlining production and eliminating upset conditions, analysts will also have visibility into the immediate impacts of making changes to the production process and will be able to build far more accurate forecasting models.

Beyond that, these same analysts will be connected to ever larger pools of data (big data) across the entire demand / supply chain that they participate in.

Industry 4.0 will give them insights into the actual product flows, but according to Centgage, in their article How Big Data Influences Accounting Today, not only will production systems such as Smart Factory Analytics and ERP systems be connected, but companies will see the value in pooling other data sources such as CRM data and possibly even payroll data. Sales data pulled from the business that sells the final products could be passed upstream to key suppliers in order to enable them to forecast far more accurately, and respond far more quickly to new business coming in the door. 

In their companion article, Big Data and Financial Reporting, they note “because Big Data pulls in information from so many places, it would be nearly impossible to spot trends using spreadsheets and simple or traditional reporting techniques. However, when Big Data is combined with other analysis tools like business intelligence and financial dashboard reporting, trends become apparent quickly that would otherwise go unrecognized. Business leaders are able to see the interplay of otherwise disconnected data and the impact it has had on their financials while also creating a more accurate predictive model that can be used in decision making going forward.”

The upshot here is that your investment in Smart Factory Analytics, while proven to have short ROI times, will also become a cornerstone of managing your business moving forward. Real time production insights will evolve into machine learning-based predictions and ultimately connectivity across the supply chain.  Using big pools of data,  businesses will improve their ability to forecast, to respond quickly to changes in economic conditions, demand signals and supply bottlenecks. They will also improve forecasting and make budgeting more and more accurate.

 

Interested in beginning your IIoT to Big Data journey? Here's an easy way to get started!

 

 

Want to learn more?
Download the ebook
Related blog articles

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
23
Oct 2019

How To Know If You Are Receiving Reliable Data from Your Production Line

English
15
Sep 2020

Why It’s Time to Prioritize Your Manufacturing Data Collection

English
30
Dec 2020

What’s Affecting Your Performance with Real-Time Data and KPI Tracking

English

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
30
Jul 2024

Qu'est-ce que la cadence dans le secteur manufacturier

À l’aide d’exemples concrets et d’informations pratiques, découvrez pourquoi calculer et monitorer la cadence sont votre voie vers une production optimisée.

French
3
Jul 2024

L’industrie 4.0 : l'avenir de l'efficacité opérationnelle avec Worximity

French
3
Jul 2024

Comment analyser la cadence

La cadence est une mesure importante des performances de l’usine. Non seulement elle indique si l'usine peut répondre à la demande des clients, mais elle constitue également un indicateur de l'efficacité globale de l'usine.

French