Spend Data warehouses have long been in vogue; it is only lately that people are questioning
the value of information they are able to garner from within. Sourcing managers face
humongous challenges in getting meaningful insight that can help them design better
sourcing strategies. Their primary operator today is 'gut feel'. If they want to leverage
in-depth visibility, measure and track enterprise sourcing performance on a continuous
basis, the road leads to a dead-end!
For years, CIOs have grappled with the problem of dirty customer data. Realizing the value
of data, they have leveraged tools and technologies from ETL and specialty data cleansing
vendors to fix the problem. Having solved the customer data challenge, they are now staring at the problem of dirty “spend data”; this refers to the universe of transaction
descriptions (stored in disparate A/P and e-Procurement systems), P-card transactions,
catalog descriptions, vendor master and ERP material master items. What is the challenge
in “spend data”? Why can't we leverage traditional tools to give the sourcing and purchasing
community what they want? To understand the limitations of traditional data-cleansing
technology, and why “spend data” requires the use of special algorithms, we need to start
with the basics. |
