Data, data everywhere but not a bit to use

I was recently reminded, as we are doing our own financials, that dirty data is the bane of any Business Intelligence or Activity Based Costing implementation team. It seems that there is a wealth of data available but if it is not clean or validated it adds significantly to the overall implementation process. It has been my experience when drafting implementation plans for large ABC projects that we allow quite a significant percentage of time (could be up to 33%) to find, source and cleanse data and develop automated processes so this can be easily replicated each update period.

I could rattle off numerous examples of bad data issues we have struck, everything from millions of dollars of explosive ordnance allocated to a child care facility (yes its true) or a one person office that was supposed to have four periscopes hidden under his desk somewhere. In both cases it was a data entry error and data entry errors are very common, particularly if there are no specific instructions on what to do in a particular situation, or if it requires manually typing in a string of alpha-numeric codes.

So how can you fix it? I'm a big proponent of fixing data issues at the source, there is no point going to the huge effort of cleansing and rectifying the data in your BI or ABC model if this is not fed back to the source data owners, because the same issues will occur the next update cycle. There are also basic improvements that can be made to data entry screens, like removing the requirement to enter strings of identifying characters and simply allow them to choose from a drop down menu.

Also it has been our experience that simply implementing an ABC model is excellent feedback on data quality issues. Because the model results are pushed out beyond the finance department to those with budget responsibility they start to see all costs that are allocated to their area, not just their budget. If the Engineering Faculty is suddenly lumbered with a large facility depreciation cost, and that building actually belongs to the Business Faculty then they are quick to point this out, particularly when these reports are transparent to senior management.

Data quality has always been and continues to be an issue for all types of BI, BPM, CPM, ABC any type of Management Information system, some keys to improving this process:

• Make the systems transparent - do not build a magic black box
• Push the results of the system out of the finance department down to lower levels of management, this provides important feedback
• Make changes at the SOURCE not in the BI, ABC system.

Cost Control in Higher Education

Just came across this white paper online it provides practical steps that can be taken by Colleges and Universities to take control of your costs. It discusses options like:

• Outsourcing
• Limiting Legal and regulatory exposure
• Limiting undersubscribed classes
• Leveraging Technology
• Addressing the costs associated with athletic programs

The full whitepaper can be found here: Cost Control in Higher Education.

Welcome to Cost Wise College

Welcome to our new blog site, this site is linked to our website http://www.costwisecollege.com/ (coming very soon) and has been developed to provide us with the ability to quickly share our stories, experiences and successes implementing cost, performance and predictive models in the higher education sector.

Why did we focus on higher education? Well there were a number of compelling reasons, but primarily there was a sudden demand for our services in Australia and here in the U.S. a report was released by the Department of Education "A Test of Leadership - Charting the Future of U.S. Higher Education" which outlined a range of issues facing higher education here in the U.S. with a primary factor being that the cost of education has been rapidly rising and this needs to be controlled so that more people can attend universities.

I personally have had a great deal of experience with implementing large scale, complex cost and performance models inside Government organizations for about twelve years now, boy has time flown by. The benefit of this experience is that we have had to create solutions to meet the unique requirements of our Government clients and make sure it was done cost effectively.

It amuses me (and equally concerns me when I'm signing up for a contract - maybe more concern than amusement) that some clients want to have everything all at once. They want to migrate from their manual data collection system with 1970's mainframe technology to a fully blown automated, near real time, Business Intelligence environment that will not only help with better business decisions but also brew their coffee and forecast the next 10 years of winning lotto numbers. This is more disturbing when some of the fundamentals haven't been resolved yet, like where is our money going? What are our outputs? Are we making or losing money? Yes this is true for Government organizations as well, particularly for Internal Transfer Pricing, or in the case of our Military clients - Foreign Military Sales.

This is equally true for Not For Profit Universities, there has to be a fundamental understanding of what's coming in and what's going out and how do you effectively budget and forecast for next year. These solutions do not have to be big bang solutions either, there have been far too many reports of large scale, very expensive IT projects that have run well over time and budget. It is our objective to ease the client into solutions, starting with some pretty fundamental issues like consolidating all the data into one area, we certainly don't need a near-real time Extract Transform and Load (ETL) solution to accomplish this, particularly if the current way of doing this is to manually collect from a range of various sources over a period of a month and then take another week to massage it in Excel. It has also been our experience that IT folk get very nervous when you dare suggest plugging into their servers, so most of the time the data is sent to us in a text file, excel format, XML format etc. basically any way works for us, as long as it is consistent.

Anyway, we can get into the detailed intricacies of data collection, cleansing, model building, cube building, report drafting, dash board creating, predictive modeling at a later date. I just wanted to take this time to welcome you and to set up the foundation for what is intended to be a collaborative type environment, so please feel free to comment on this post and to ask any specific questions you may have or are facing in relation to the wonderful world of cost and performance modeling.

Cheers,

Lea Patterson