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Business Intelligence (B.I.) in MPS

3 Sep, 2013 By: Antonio Sanchez Navarro, Nubeprint


Artificial Intelligence (A.I.) is defined by Wikipedia as “a system that perceives its environment and takes actions that maximize its chances of success.” (http://en.wikipedia.org/wiki/Artificial_intelligence).

MPS is about managing from remote printers and copiers. Therefore, the analysis of the environment in which each device works is the responsibility of a tool (the MPS software tool) that has to make recommendations for the dealer to deliver the supplies, send the technician and bill for the actual number of pages printed. The MPS software uses the data available at the printer to identify the needs. But not all printers or copiers are normalized for MPS (I may even say that there is still not a single printer model that is 100% compliant).  If the data is not available or incomplete, the software may be useless and the dealer is forced to ask the printer user to manually request the cartridges, or services, or even to communicate the page counters. The costs of managing MPS climbs sharply as the accuracy of the service declines, the control of costs vanish. Hence, the dealer's risk increases sharply.

There is a global belief that newer printers and copiers are more MPS compliant. Alas, the reality is that the manufacturers do not evolve homogeneously: while the new models of a few manufacturers show a relevant evolution towards a better MPS compliance, the trend of others are moving in the opposite way.  Therefore it is not realistic to assume that the dealer will be able to reduce his/her risks in MPS via only selecting specific hardware manufacturers or even models (more details available in the Nubeprint report published twice a year at www.nubeprint.com). The need for accurate information and decisions around MPS is solved by embedding intelligence (A.I.) in the software tool that drives MPS.  The built-in A.I. identifies the degree of MPS compliance of each one of the printers that must be managed, and adapts to the specific individual needs.

The role of A.I. in MPS is the following:
 

•        Fill the gaps: not all printers provide the current levels of all the supplies needed. But the dealer needs all the levels in order to identify what he/she needs to ship and when. The A.I. module will identify what is missing and builds it.

•           Filter the data: the behavior of the printer makes a monitoring tool duplicate or triplicate the same alert. The intelligence built in filters this to ensure the highest accuracy.

•           Take accurate decisions: the decision to ship a cartridge is based on how real the need is, is it the right moment to deliver and can it be delivered together with other cartridges.

•           Measure inefficiencies: 99.9% of the MPS contracts signed require multiple players apart from the dealer (the end-user, the technician, etc.). The A.I. module coordinates all their tasks and measures how efficiently each one is contributing.

•           Measure overall profitability: the whole purpose of MPS is to have a professional organization (the dealer) assuming the traditional role of the end-user and to do it much better. The intelligence of the process has to measure to which extent the delivery of service is better or worse compared to expectations: how much operational profit is this activity generating.

•           Provide value added information to improve the dealer's MPS offer: the information that an A.I. embedded MPS tool (like an MPS yield management tool) generates is huge. Indeed it is so great that the dealer would do very well to combine it with a Business Intelligence tool to take advantage of all of it.

As a result, the dealer is then able to provide MPS services. This translates into managing the printers of the end-customers much better than the customers themselves in order to achieve the SLA commitment. Among the goals that the dealer must have, the following are the most relevant:
 

•           Minimize the waste of toner:

o          Each cartridge is used to its maximum capacity (consequently the number of cartridges used per printer can diminish by more than 30%);

o          Recuperate all of them for a proper disposal or recycling (environmental regulation);

o          To reduce the emissions of CO2 (environmental regulation);

•           Predict the needs of supplies and service in order to:

o          Reduce the stocks of supplies

o          Minimize the costs of deliveries

o          Plan the visits of the technicians and ensure that the up-time of each printer is 100%.

•           Managed the assets: availability, retirements and replacements.

•           Automate the invoicing activity.

•           Optimize processes that have an impact over a plurality of stakeholders and processes:

o          End-customer: the dealer must put in place an auto-fulfillment process that makes it unnecessary for the need of the customer to call when a printer is low of toner, or when it requests a new waste bottle or a fuser. (The end-customer fully outsources the management of its printers and copiers). Therefore, truly planning the deliveries in advance (no more urgent deliveries, nor individual deliveries).

o          Costs of stock: the dealer must have accurate predictability of the needs of its customer's printers. Underage and overage costs are then reduced to nil. The stock is sized according to the short term needs, and its turnover is accelerated by 100% or more.

o          Acquisition costs: the dealer knows months in advance the needs for spare parts. He/she can then negotiate much better prices with the distributor by notifying those weeks in advance of what and when the supplies will be needed (and saving the distributor the need to stock them).

o          Servicing costs: the usage of predictability can be extended to technical needs. The dealer can diminish the visits of a technician. It is known that 90% of the visits of the technician can be avoided or planned. The efficient usage of an MPS yield management tool may show results as high as a reduction of visits by 45%, and the possibility to reduce the non-planned visits to only 10% technical visits provided by the dealer.

o          Back office: the implementation of MPS multiplies the amount of information that the dealer manages. It quadruples the number of incoming calls from customers, converts the billing cycle into a nightmare, and any possibility to control the efficiency of the business blows up. On the opposite side, A.I. yield management tool predicts the needs from the printers. As a consequence, it reduces the incoming calls to close to nil, shortens the billing cycle to hours, and keeps the whole process controlled under an earn value analysis approach.

The dealer has multiple software applications in place (ERP, Business Intelligence, Accounting, etc.). The MPS tool is an added one. Though some (like the ERP) may have an embedded A.I. system, none can replace a dedicated MPS tool. This business is so specific that in order to manage it the dealer must have a focused MPS yield management tool. MPS is not about selling, it is about reducing costs to maximize the efficiency. It is about doing ordinary things extraordinarily well. A player not understanding this little difference will hardly succeed in MPS, and will soon feel the frustration of being in a business that he/she does not control.

Antonio Sanchez Navarro is the founder &  President of Nubeprint, a leader in incorporating Artificial Intelligence to the management of output devices. His background includes the HP Financial Services division; leading worldwide strategy to address MPS from HP FS. He developed no less than 5 patents including hardware and software becoming pioneers of the vendor agnostic MPS service; incorporating Artificial Intelligence in the MPS Market, and more (full bio in “About Author.”).  Visit http://www.nubeprint.com




About the Author: Antonio Sanchez Navarro


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