Management Information Systems

MBAB5P09

Dr. Anteneh Ayanso

Part II of Assignment I

Analyzed and Compiled by -

| Zhang, Ivory | Borah, Pari | Krysta, Peter |

| Chen, Bi l l ie | Baidwan, Karan |

Introduction / Context

HF Commercial Equipment Finance wishes to observe its Electronic Payment

System’s adoption trends across their clientele of 4000 customers. The

customers use various forms of f inancial products such as loans, traditional

and structured leases, etcetera from HF.

Historically businesses have been shy in adopting an electronic payment

system for handling transaction between businesses. Some of the key reasons

for this have integration constraints of IT infrastructure into the existing

system, inability of trading partners to send and receive automated remittance

information, a slow learning curve with a general diff iculty in convincing

customers and supliers to switch over to EPS. However in recent times, the B2B

market has seen a growing acceptance of EPS among its merchants with new

advances in technology especially areas of security. A good example is

Alibaba.com, China’s leading online trading platform for merchants. Its 2014

IPO is predicted to surpass that of Amazon.com.

The objective of this report is to ascertain the trends of EPS adoption that exist

among HF’s customers on the basis of certain attributes of the collected data.

The data is examined in multiple dimensions with cross tabulations, pivot

tables, and pivot charts to examine if relational trends exist between any

possible pair of those attributes in order to better direct our marketing and

other promotional strategies to improve EPS adoption among HF’s customers.

Methods UsedThe EPS acceptance rate for each individual data attribute (ex- Paydex,

Industry type) was examined. Based on this data, a further multi-dimensional

analysis of a combination two different attributes in terms of EPS acceptance

was observed for possible indications of trends. Some of the attribute

combinations that were looked into are EPS acceptance in terms of number of

schedules and product type, or EPS acceptance in terms of region and number

of employees, etc.

Observations from Analyses

Out of 10 industry types , the Transportation, Communication and Util ity

industry made up the largest customer base of HF with a total of 1154

companies or approximately 30% of their clientele. However , the sector,

even after comprising of three different industries sti l l has the lowest

EPS adoption rate of 24% among all other type of customers. The same

can be said also for Service and Wholesale industries which make up

approximately 9% and 8% of the customers but have adoption rates of

only about 34%. In comparison, the Agriculture, Forestry and Fishing

industry makes up less than 1.5% of the total customer base has an

impressive adoption rate of almost 40%.

In term of number of employees , the surface it looks l ike there is a

fairly uniform distribution of EPS penetration across all sizes of

companies. However the sudden spike in medium scale (50-250) to 41 %

may be indicative of a bell curve l ike distribution of EPS. If so, further

appropriate statistical analyses can be performed for a precise picture.

When it comes to region , Midwest, Southeast and Southwest regions

have a very low EPS penetration compared to other regions.

In general customers with higher number of schedules (products) have

higher EPS usage but this number dips after 20 or more products. This

has proven to be consistent in all two dimensional analyses. A more

concise picture is presented when the analysis is conducted with region

and type of industry.

When it comes to type of product , lease and quasi products have half the

penetration of EPS compared to Loan and Multiple products. This is

better examined in cross tables of product types with region and

industry type.

Based on information available at

http://mycredit .dnb.com/glossaries/paydex we have categorized the

customers into three Paydex Risk groups. The risk is indicated by the

duration in which the payments are made to HF.

Both high and low risk groups have a lower adoption rate of EPS

compared to the group of medium risk profile customers.

Implementation of EPS into their business systems will significantly

reduce the duration of credit and hence bring down risk for all

customers overall .

In terms of Average previous Payments, companies with a history of

higher payments have a higher adoption rate of EPS. Cross tabulated data

presents this information more precisely across other attributes such as

region, size of the company, number of products purchased, etc.

Cross Tables

For Type of Industry vs. Number of Schedules , there is a steady

increase in EPS usage among small scale companies as number of

products sold increase. The same can be said for medium scale

companies. Small-scale companies however have an erratic distribution

of EPS adoption.

For larger purchases of 20 or more products, large scale companies show

a sudden decline in EPS rate. This behaviour is consistent when EPS

usage for number of schedules is compared against a number of other

attributes.

For Industry Type vs. Region there is highest penetration in the mining

industry. While the Midwest region suffers in terms of EPS penetration in

a number of industries with marginal penetration figures in

construction and manufacturing industry

For Region vs. Product Type , loan and quasi products have a very low

eps penetration in midwest and southwest regions. They both are

mutually responsible for each other’s poor performance.

EPS adoption for Type of Product vs. Type of Industry shows that in

the Services industry, product type Quasi has lowest EPS penetration and

hence should be examined. In Transportation Communication and Util ity

industry, Lease and Quasi product types have lowest EPS adoption rates.

Lease products may have a greater scope for improvement as there are

509 companies yet to deploy EPS. The Quasi product however should not

be a major area of concern as there are only 26 companies that use this

product and do not use EPS.

Conclusion:

Lease and Quasi type products have not been able to attract customers

towards electronic payments in the Midwest, Southeast and Southwest

regions.

Transportation Communication and Util ity despite of being the largest

customer base of HF has the least EPS adoption rate.

High and low risk groups seem to shy away from using EPS methods in all

attributes, this is mainly because of their volume of purchase both in

terms of their cash worth and quantity, and also the type of products

purchased.

Product volume quantity and product type also seem to be the key

factors in EPS adoption in terms of average previous payment of

customers.

Bibliography:

http://www.prnewswire.com/news-releases/b2b-electronic-payments-

growing-58783427.html

http://www.itbusiness.ca/news/3-predict ions-for-b2b-e-commerce-in-

2014/45891

http://ieeexplore. ieee.org/xpl/ login. jsp?tp=&arnumber=4958934&url=http

%3A%2F%2Fieeexplore. ieee.org%2Fxpls%2Fabs_al l . jsp%3Farnumber

%3D4958934

http://www.dovetai lsystems.com/pdfs/

Dovetai lWhitepaper_RisingTideOfUSElectronicPayments.pdf