Interrelationships Of Information Technology And Research Proposal

Length: 14 pages Sources: 6 Subject: Business - Management Type: Research Proposal Paper: #64694668 Related Topics: Information Technology, Fresh Direct, Transparency, Customer Expectations
Excerpt from Research Proposal :

The efficiency gains from BPM and BPR must be oriented towards a specific strategic objective to be effective (Attaran, 2004).

While processes are often continually monitored to see how they can be made more efficient to save on costs, it is has been shown that re-orienting processes to be more customer-centric can transform entire companies. The concept of a Demand-Driven Supply Network (DDSN) (O'Marah, 2004) specifically focuses on this level and focus of interprocess integration and re-orientation. As with the Toyota Production System (TPS) the concept of a DDSN in the context of any organization is to create higher levels of transparency and trust through shared process ownership. From this context both the Toyota Production System and DDSN model share the attribute of collaborative workflows that ensure higher levels of adoption and higher levels of accuracy as well (O'Marah, 2004).

Like the Toyota Production System, DDSNs are capable of becoming learning ecosystems (Dyer, Nobeoka, 2000) due to the intensive level of interprocess and system integration that is prevalent in these approaches to managing collaboration often on a global scope. The use of DDSN as a strategy for ensuring customer-centric processes gain the highest priority and also attain the highest levels of performance over time are critical. In fact the combining of the TPS concept for supply chain integration to the process level with the DDSN concept for demand management and customer-facing processes could be used for defining entire value chains in an organization.

Quantifying the extent of interprocess integration on the financial performance of an organization is a concept mentioned in the Introduction of this analysis. The Perfect Order (Novack, Thomas, 2004) is a key performance indicator companies rely on to verify and measure over time the extent of interprocess and system -- level linkages over time. Quantifying the performance of supply chains and their ability to stay focused on the goal of being demand driven is also captured in this metric. Ultimately The Perfect order metric is useful for measuring the accuracy, stability, transparency and trust generated throughout a supply chain (Columbus, 2008).

Measuring Interprocess Integration and Management Linkages in Supply Chains

Organizations have created process-based linkages in the form of connections that are rapidly becoming knowledge sharing networks (Dyer, Nobeoka, 2000). The corresponding growth in measuring the accuracy and performance of these networks on transaction accuracy and velocity is how The Perfect Order metric of performance (Columbus, 2008) has gained in prominence. In essence The Perfect Order measures the extent to which the process linkages throughout a supply chain are delivering consistently accurate and consistent performance (Novack, Thomas, 2004). One of the key factors in the growing popularity of this metric is the ability to quickly assess the impact of internal and external factors on the entire supply chain networks' performance. It is in effect a measure of the performance of a supply chain taking into account the key premises and concepts of Chaturvedi (2005).

For any company to attain excellent performance on the Perfect Order there are many other supply chain metrics that need to also be synchronized. The true objective of completing any level of supply chain interprocess synchronization is to ensure the highest level of responsiveness to customers. This is consistent with the core concepts of the DDSN model as mentioned earlier (O'Marah, 2004), yet seeks to extend this concept by including order velocity as a function of interprocess integration. Table 1, Measures of Supply Chain Performance, provide a summary of the most often used series of metrics by manufacturing and services companies alike in their pursuit of attaining high levels of performance on The Perfect Order measure of performance.

The Perfect Order is a measure of how effectively an organization has also been able to align its internal processes to their strategic plans. Not only does this measure of performance indicate the level of interprocess linkages and their correlation to management strategies, it actually measures how effectively the connections work. Inherent in any supply chain there is the need...


The Perfect Order is used as a means to share ownership of these key process areas and give each supplier in a supply chain network an opportunity to evaluate their performance. Each of the cycle times shown in Table 1 are often used as predictive indicators of how effective an entire network of suppliers are managing customer-facing processes (Columbus, 2008). This metric also shows the increase in accuracy based on interprocess transparency as well.

Table 1: Measures of Supply Chain Performance

Measure of Performance

What It Measures

Perfect Order

An order that is complete, accurate, on time, and in perfect condition

Demand Forecast Accuracy (DFA)

The difference between forecasted and actual demand

Quote-to-Cash Cycle Time

The time between when a quote is accepted by a prospect to when their first invoice is paid

Cash-to-Cash Cycle Time

The length of time between when a company spends cash to buy raw materials to the time cash flows back into the company from its cus-tomers. Includes the following metrics:

Ship to Customer Delivery -- Time taken from shipment of finished goods to delivery at customer's address Raw Materials

Receipt to Payment -- Time from receipt of raw materials to payment; also called Days Payable Outstanding (DPO)

Days Sales Outstanding (DSO) -- Measurement of the average collection period from invoicing to cash receipt.

Supply Chain Transparency and Performance

Integrating customer-facing systems with supply chain, ERP, fulfill-ment and service systems gives manufacturers the ability to track their progress toward a Perfect Order. These metrics include:

Available-to-Promise (ATP) -- Defines for both standard and customized products when the shipment will occur.

Capable-to-Promise (CTP) -- Defines stock levels relative to demand to the purchase order level.

Order Visibility -- Provides both at the individual order level and an aggregate view new order activity and its implications on the supply chain, existing production schedules and fulfillment.

Supply Chain Management (SCM) Cost

SCM cost includes the following components:

Direct purchasing operating cost

Manufacturing operating cost

Transportation cost

Warehouse/distribution center operating cost

Inventory holding cost

Customer service operating cost

Sources: Hofman (2004); Cecere, L., Hagerty, J., Souza, J. (2005)

The Impact of Interprocess Integration on Financial Performance

Measuring the efficiency of any given process is going to be largely attributable to the extent to which specific interprocess functional areas are accurately and reliably mapped to each other. Yet to carry this measurement of linkages from a process-centric view to one that captures their financial performance is one that requires accurate benchmarking of customer-facing metrics (O'Marah, 2004). The use of The Perfect Order, with its heavy emphasis on integration at the process level serves as a starting point to measure the financial performance of interprocess linkages (Columbus, 2008).

Table 2: Financial Performance Outcomes of Interprocess Performance

Areas of Measurement

Baseline: What to Measure

Example of Benefits


Project costs and expenses

Use as a baseline for defining ROI

Number of orders per year

Determine configuration's impact on inventory turns

Current inventory and costs

Inventory turn savings

Customer data

Lifetime cost per customer; average deal size by customer


Order cycle time

Order cycle times reduction of 65% or more recorded with mftrs. contacted

Cost of Sales

Days Sales Outstanding reduction from 60 to 29 days on average

Cross-sell and up-sell revenue

Increase of 33% on aggregate

Average sales price per order

Increase from 9% to 26%

Quote and Order

Average costs to complete an order

95% reduction in cost per order

Special pricing requests

Over 100% ROI on automating Special Pricing Requests

Bad or incomplete orders

Incomplete order reductions of 20%

Customer Service

Number of customer complaints

98% reduction in cost of simple requests

Revenue lost to churn

60% when cross-selling is used with quote-to-order

Number of calls on order status

Median level of 500 per week to 70

Warranty and Returns

Reduction in warranty cost on customized products

10% reduction at a minimum

Labor cost reductions

Decrease order re-work from 15% to 2%

Over time the financial results of The Perfect Order are reflected in the baseline figures shown in Table 2, Supply Chain Strategic Measures of Performance. These measures of performance are most influenced by a synchronized and consistent supply chain strategy. In effect they quantify the linkages as mentioned by Chaturvedi (2005). Quantifying through financial performance the knowledge networks' performance over time (Dyer, Nobeoka, 2000) also further validates how critical it is for IT to be seen as an enabler of processes, not just as a means to generate more data or information. It is in fact in the transformation of data and information into knowledge that exceptional financial performance, in this case measured by The Perfect Order, become attainable.


In order for any organization to remain financially viable today and into the future, it is critical they view processes not as siloed activities but as strategic that can be coordinated and synchronized to attain their…

Sources Used in Documents:


AMR Research (2003) -- Configuration is the Heart of Customer Fulfillment for Complex Product Manufacturers. AMR Research Report. Monday March 31, 2003.

Mohsen Attaran. (2004). Exploring the relationship between information technology and business process reengineering. Information & Management, 41(5), 585-596.

Ganesh D. Bhatt. (2000). Exploring the relationship between information technology, infrastructure and business process re-engineering. Business Process Management Journal, 6(2), 139.

Marianne Broadbent, Peter Weill, Don St. Clair. (1999). The implications of information technology infrastructure for business process redesign. MIS Quarterly, 23(2), 159-182.

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