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The Untapped Potential of Predictive Analytics in the Office Technology Channel Blog Feature


By: Scott Cullen on March 2nd, 2020

The Untapped Potential of Predictive Analytics in the Office Technology Channel

Predictive analytics is poised to transform supplies fulfillment and service operations across the dealer channel.

I’ve learned a lot about predictive analytics during the past month. And I still have a lot to learn.

But I don’t need a sophisticated algorithm to tell you it’s a complicated and evolving technology. And because predictive analytics uses artificial intelligence (AI) technology, it’s probably a lot smarter than me.

Allow me to share with you what I’ve learned about predictive analytics to date with the caveat that there’s still more to learn.

Much of what I’ve learned by speaking to those in the know is fascinating.  

Defining Predictive Analytics

Predictive analytics is a mix of statistical methods such as data mining, predictive modelling, and machine learning that analyzes current and past behaviors to make predictions about future events. Predictive models use data to identify risks and opportunities.

In the office technology space, predictive analytics is being used to enhance supplies fulfillment and create a more efficient and proactive service and maintenance organization.

Three Buckets of Predictive Analytics

One of the people I spoke to about predictive analytics was Wes McArtor, president of NEXERA, a BEI Services company. He explained that predictive analytics, as it applies to the office technology dealer channel, falls into three primary buckets:

  1. Just-in-time supply replenishment or predicting when the customer will need a supply so that it can be shipped prior to the need.
  2. Monitoring devices on the network to prevent service calls or provide proactive service.
  3. Monitoring and managing computer networks via a Managed Services offering to provide proactive service and reduce onsite service calls.

Predictive Analytics for Supplies and Fleet Management

Virtulytix, a consulting company focused on predictive analytics turned out to be another excellent source for learning about the topic. I don’t want to turn this into a commercial for Virtulytix, which has a product called Supplies IQ which monitors devices and predicts when a cartridge will be empty using predictive analytics, but this is an excellent example of what the technology can do. 

Indeed, supplies and fleet management are key areas where predictive analytics can make a difference, particularly in MPS engagements.

“When we talk about predictive analytics, we're talking about building predictive modeling systems that can take data and ingest it in real-time or batch mode,” said Ed Crowley, president of Virtulytix.

The most common predictive analytics model for supplies fulfillment, according to Crowley, is one that uses a linear algorithm to estimate how many days until a cartridge is empty.

For example, a cartridge has been in a device for two months and two thirds of the toner has been consumed. Using a linear model, the analytics would indicate that there is one month’s worth of toner left in the device. But not so fast. That might not be accurate.

Virtulytix uses various statistical and analytical models for each cartridge and then predicts when the toner cartridge will be empty, based on that information.  

For example, it’s March 1 and the analytics, based on past data, show that the device is rarely used after March 15. Using this predictive analytics model, the cartridge won’t run out of toner for another six months because the device has entered a historical period of low usage. What this predictive analytics model does is take the device and user behavior into account when determining the best time to send the customer a new cartridge.

“Almost every cartridge, every user has abnormal behavior, because there is no normal behavior,” said Crowley.“  It fluctuates all over the place.”

For dealers managing a fleet, it’s important that they ship a cartridge just in time.

“If it's shipped early, about 89% of the time, the customer will replace the cartridge when they receive it, regardless of how much toner is still in the cartridge,” said Crowley. “On a managed service contract, with page-per-use, that costs dealers a lot of money.”

Predictive Analytics for Service Maintenance

Predictive analytics can reduce service costs and downtime by predicting when a device will fail and how it will fail. Understanding that, a service provider can proactively prepare for these events before they occur.

Using predictive analytics for service has the potential to reduce the number of service calls through service route optimization and improve First Call Effectiveness (FCE) by diagnosing root causes. It can also optimize parts inventory. Crowley says this can reduce service costs by as much as 20-25%.

Monitoring devices using predictive analytics can eliminate multiple service calls to the same location or customer site. Rather than waiting for the device to fail under a reactive service model and then sending a tech out to fix it, then going back the next day to fix another device, a dealer can identify in advance all the devices that are going to fail within one to three weeks and then send a service tech out to repair those devices on one call, saving the dealer money. So, instead of it being four hours of the service tech’s time, it may only be one hour.

The more proactive and efficient a service department is, the more satisfied the customer and the more cost efficient it is to service that customer.

The OEMs and Predictive Analytics

I am only scratching the surface about predictive analytics. And I’m learning more every day. At the recent HP Analyst Meeting in Palo Alto, the company discussed its smart device services platform and how it is adding sensors to just about everything inside those printers. Can you say predictive analytics?

“With data available on MFPs, technicians, and training, dealers will be able to use fleet comparisons to identify problems before customers or costs are affected,” said Gregg Gumpright, director of services and support for Sharp Imaging and Information Company of America, in an email reply to my questions about predictive analytics. “Dealers will be able to discover whether an issue lies with machine mechanisms or human error and when it is cost-effective to incorporate further training for a technician or remove and repair a machine.”

Bottom line: The OEMs, not just HP and Sharp, are on top of predictive analytics.

What’s Next for Predictive Analytics in the Office Equipment Space?

Not to get too far ahead of ourselves because predictive analytics has not yet become firmly entrenched in the channel, but there are opportunities for the technology beyond supplies fulfillment and improving service operations.

For instance, predictive analytics can be used to predict sales behavior and customer behavior. Some might describe the latter as consumer modeling or marketing predictive analytics. This can be used to identify the right type of customer for the dealer’s products and services and can identify the customer’s buying behavior.

In the meantime, Crowley views predictive analytics as a survival tool for the dealer channel.

“Our industry has been blessed and cursed by high-profitability. We've been able to run fairly inefficient businesses because of the incredible supplies margins and supplies annuities for decades and not worry much about how efficient we are at doing things. That's changing.”

From what I learned in my initial research on this topic, he’s spot on.

Scott Cullen

Scott Cullen is regarded as one of the most respected and longest tenured journalists in the industry. Throughout his distinguished career, Scott has contributed to numerous business and technology publications both inside and outside of the industry. In February 2016, Scott joined The Cannata Report as managing editor and chief correspondent and in October of 2016 was named editor in chief, his true dream job.  Since joining The Cannata Report, Scott has accentuated breaking news and related follow-up coverage and analysis across The Cannata Report’s digital platforms. He has introduced substantial editorial coverage of business modeling, software, IT and other professional services and enhanced coverage of product and vendor news. A pop culture enthusiast with a passion for music, movies, baseball, and women’s basketball, when Scott’s not writing about the document imaging industry or traveling to an industry event, you can usually find him at a concert or sporting event somewhere between Philadelphia and New York City.

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