Posts Tagged ‘MDM’

The butterfly effect on enterprise data within SCM

January 2, 2013

After doing a couple of projects where master data was a critical element but unfortunately nothing was done to correct it, I thought that I would reintroduce the post on the Butterfly effect in Master Data. All to often the master data is completely forgotten in projects and in the end costs money to rectify and could lead the software to fail after go live. So to learn more about the butterfly effect and it’s impact on master data read on!

The term “butterfly effect” refers to the way a minor event – like the movement of a butterfly’s wing – can have a major impact on a complex system – like the weather. The movement of the butterfly wing represents a small change in the initial condition of the system, but it starts a chain of events: moving pollen through the air, which causes a gazelle to sneeze, which triggers a stampede of gazelles, which raises a cloud of dust, which partially blocks the sun, which alters the atmospheric temperature, which ultimately alters the path of a tornado on the other side of the world.

Enterprise data is equally susceptible to the butterfly effect. When poor quality data enters the complex system of enterprise data, even a small error – the transposed letters in a street address or part number – can lead to revenue loss, process inefficiency and failure to comply with industry and government regulations. Organisations depend on the movement and sharing of data throughout the organisation, so the impact of data quality errors are costly and far reaching. Data issues often begin with a tiny mistake in one part of the organisation, but the butterfly effect can produce disastrous results.

An ERP or supply chain system focuses on parts, descriptions and inventory data. Since government agencies don’t control the way supply chain and ERP data is defined, you may not have an idea about how the data should look in an ideal state, but it should provide an accurate depiction of the physical warehouse or just-in-time supply chain system. You need to know what is in stock, when it can be supplied and how much it costs.
Holding just the right amount of inventory is crucial to optimising costs. After all, inventory costs are incurred every hour of every day in areas including warehouse storage, heat and electricity, staffing, product decay and obsolescence. With this in mind, consider the impact of a transposed letter in an ERP system. Someone enters part number XL- 56YJM instead of LX-56YJM. Until the error is discovered and corrected, you may hold duplicate parts in inventory or not be aware of parts carrying the slightly different SKU because of the transposed letter.

You also want to take advantage of volume discounts. If the data is unstructured, making it difficult to understand global buy patterns, the company may miss out when negotiating with the vendor.

Because there is no standard format for ERP data, few of the steps for fixing the data are done for you ahead of time. It is critical to establish a methodology for data profiling in order to understand issues and challenges. Since there are few governing bodies for ERP and supply chain data, the corporation and its partners must often come up with an agreed-upon standard, with input from users of the data to understand context, how it’s used, and the most desired representation.

If you have clean data in your supply chain, you can achieve some tangible benefits. First, the company will have a clear picture about delivery times on orders because of a completely transparent supply chain. Next, you will avoid unnecessary warehouse costs by holding the right amount of inventory in stock. Finally, you will be able to see all the buying patterns and use that information when negotiating supply contracts.

Advertisements

Procure-to-Pay, tips for the Enterprise

November 12, 2012

As more companies are seeking to move beyond procurement into fully deployed supply chain systems, a key challenge for many companies is in the area of improving efficiency in their procure to pay cycle for many of their contracted services, especially in the area of facilities maintenance and on-site contract management. There exist multiple challenges in environments where field associates are working from manual or electronic systems, requisitioning on-site services for maintenance or other activities, and ensuring that this information is captured effectively. In addition, there exist significant challenges to ensure that the proper service level agreement is fulfilled, the correct price is charged, the purchase order is transmitted correctly, the invoice matches, and finally, that the supplier is paid the correct amount for the actual services delivered. While many enterprise systems claim that these elements are simply defined within their structural logic, the truth is that there are plenty of opportunities for error, and that without a planned process for managing the procure to pay cycle, the organization may be bearing significant costs due to non-compliance to system or process requirements.

So here are a few tips that should help

• Develop common processes and procedures for the P2P process, and roll-out training at site level to ensure that people are comfortable with the approach. Be prepared to modify minor elements the process to accommodate site-level requirements, but keep the essential elements of the process flow intact. Emphasize the importance of this approach to the entire P2P cycle, including accounts payable, invoicing, and blocked and parked invoices. Explain the impact of lack of adherence to process – and that the supplier will not be paid in a timely manner for their work if errors occur in the process.
• Improve master data robustness and integrity. Whether this involves ensuring proper audits of external vendor catalogs, or internal content management, clean master data is a mundane but critical element to supply management and P2P best practices. Minimise opportunities in the P2P process for keystroke and free text errors to occur, by error- proofing the system and mapping the process to identify where errors are occurring. Recurring training will also ensure that errors are reduced.
• Explore punch-out roundtrip and other approaches to exploit external content management approaches. This is especially important to ensure that the most efficient buying channel is selected.
• Exploit the use of procurement cards for high transaction volume, low transaction value purchases. Pcard technology has evolved significantly, and companies need to identify opportunities for hard dollar savings through this approach via rebates.
• Be sure to update master data and pricing rates on an on-going basis. In particular, attention should be paid to units of measure, appropriate industry-standard nomenclature, updating of labor rates based on market conditions, and on-going clarification of requirements against existing contracts.
• Establish how you are buying products and services, and document the buying channels through which these purchases are occurring. Inevitably, you will discover that purchases are occurring through improper or less- efficient channels, which is detracting from your team’s ability to engage in strategic value-added approaches. Get out of the transaction management business! To do this, you need to establish standard processes and procedures, and commit to a change management plant to ensure that people are using the right buying channels for the different types of spend.
As technology and business requirements evolve, the P2P cycle will certainly need to be re-visited from time to time to ensure it is meeting the needs of internal customers, and that suppliers are satisfied with the system.

The Butterfly effect within the Supply Chain, Specifically Master Data Management!

October 27, 2012

The term “butterfly effect” refers to the way a minor event – like the movement of a butterfly’s wing – can have a major impact on a complex system – like the weather. The movement of the butterfly wing represents a small change in the initial condition of the system, but it starts a chain of events: moving pollen through the air, which causes a gazelle to sneeze, which triggers a stampede of gazelles, which raises a cloud of dust, which partially blocks the sun, which alters the atmospheric temperature, which ultimately alters the path of a tornado on the other side of the world.

Enterprise data is equally susceptible to the butterfly effect. When poor quality data enters the complex system of enterprise data, even a small error – the transposed letters in a street address or part number – can lead to revenue loss, process inefficiency and failure to comply with industry and government regulations. Organisations depend on the movement and sharing of data throughout the organisation, so the impact of data quality errors are costly and far reaching. Data issues often begin with a tiny mistake in one part of the organisation, but the butterfly effect can produce disastrous results.

The Supply chain system ( whatever that system may be) focuses on parts, descriptions and inventory data. Since government agencies don’t control the way supply chain and ERP data is defined, you may not have an idea about how the data should look in an ideal state, but it should provide an accurate depiction of the physical warehouse or just-in-time supply chain system. You need to know what is in stock, when it can be supplied and how much it costs.
Holding just the right amount of inventory is crucial to optimising costs. After all, inventory costs are incurred every hour of every day in areas including warehouse storage, heat and electricity, staffing, product decay and obsolescence. With this in mind, consider the impact of a transposed letter in an ERP system. A part number gets entered into the system as AB-21602M instead of BA-21602M. Until the error is discovered and corrected, you may be holding duplicate parts withinin inventory or not be aware of parts carrying the slightly different SKU because of the transposed letter.

You also want to take advantage of volume discounts. If the data is unstructured, making it difficult to understand global buy patterns, the company may miss out when negotiating with the vendor (if you can”t describe an item, you can’t buy it).

Because there is no standard format for ERP data, few of the steps for fixing the data are done for you ahead of time. It is critical to establish a methodology for data profiling in order to understand issues and challenges. Since there are few governing bodies for ERP and supply chain data, the enterprise and its partners must often come up with an agreed-upon standard, with input from users of the data to understand context, how it’s used, and the most desired representation. The most simplest standard to use is Noun, Modifier, Characteristic, works well for any industry, example Valve, Butterfly, 10 inch, 600 lb, CS, ASTM XXX etc and always make sure that the manufacturers part number is available, they make it so they should also be able to describe it.

If you have clean data in your supply chain, you can achieve many tangible benefits. First, the company will have a clear picture about delivery times on orders because of a completely transparent supply chain. Next, you will avoid unnecessary warehouse costs by holding the right amount of inventory in stock. Finally, you will be able to see all the buying patterns using spend analysis and use that information when negotiating supply contracts.

Master Data Management…..Fundementals

October 9, 2012

Data accuracy and quality can be a moving target and implementing fixes without understanding the underlying causes can be very time consuming and expensive in the long term. Data can be transient in nature,whereas other business focus areas such as processes, people,compliance and management performance indicators can change the accuracy and relevance of data. In order to get things straight Data Governance should be a priority in any organisation wish to implement any eProcurement based methodology. So what is data governance?

Data governance is a quality control discipline that covers the acquisition, management, storage and usage of information or data within a business, with the objective of maximizing the value of the organisation’s data assets. In layman’s terms, it is getting your
data and related processes in order, so that the business can derive value from it. A most recent example that I have personally come across is a company that allows anyone and all to enter descriptions into a catalogues to assist in the buying process. With no sort of Governance catalogues can very quickly deteriorate into chaos, thus leading to cost over runs and surpluses within the inventories.

The process of Data Governance can be time consuming, but the benefits to the business can be enormous. Without it businesses will continue to fight fire after fire and slowly but surely go under.