Lean techniques for Data Quality Improvement: Time Value Traps
by Dylan Jones
Many of you will no doubt be aware that organisations that adopt Lean initiatives can witness a dramatic effect on the reduction of waste in their business but Lean can also provide a major advantage to your data quality initiatives too.
In this article, the first in an ongoing series, we provide details of a Lean technique that can help you rapidly identify areas ripe for improvement.
This will help you generate immediate benefits to your customers, reduce the bottom line and get the business bought-in to the benefits of sound data quality management.
What is a time value map?
A time value map examines how time is spent in a process. It really is as simple as that.
If you take any business process in your organisation there will be activities that add value to the business and others that add cost or waste.
How do we define added value?
We identify value add activities from the perspective of the customer.
For example, if they need an order to be completed as rapidly as possible then any delays in that process reduce the perceived value of the service from a customer viewpoint.
Waste obviously adds significant costs to the internal delivery of that service as well so the business ultimately pass the costs onto the customers.
The customer therefore gets a double whammy – a slow service and a more expensive product. So they they look elsewhere.
What are the two types of waste?
We do however need to make the distinction between wasted effort and required waste.
Financial institutions for example may have to complete additional regulatory paperwork that adds no value to the customer but is essential nonetheless.
What we are really looking for then is opportunities to find the areas of waste that our data quality initiative can address at minimal cost for greatest return but first we need to know where to look.
How do we construct a time value map?
Simply track any item of work as it flows through a key business service such as order handling for example.
Create a chart for each activity detailing how long the activity took (in minutes) and whether the activity was:
- Value added
- Required waste (eg. regulatory)
Identifying wasteful activities can be quite challenging. For example, there may be a batch job to collect and process orders. You could consider this value added – we’re getting the job done aren’t we? But in the eyes of the customer this really isn’t the best use of time, you’re not physically adding any value just another time trap.
Once we have the full list of activities and their times we can construct our time value map as shown below.
How do we provide focus for data quality improvement?
So we now have a simple visual map of where to focus our data quality efforts by examining the activities in the “red zone” but will this wasted value be connected to poor data quality?
In many cases it’s a definite yes.
Data quality issues in the service chain can be a major cause of non-value added time creation. Most organisations “waste” a major portion of their income to funding additional staff to handle complaints, chase missing records, deal with anomalies and generally clean up the mess poor data quality leaves behind.
However, be prepared to uncover a whole range of additional business and technical issues as you unravel the complex service chains that are the fabric holding your business together. Quite often, a complete process re-design is required, data quality may be only one part of a very large puzzle.
Extend your data quality key performance indicators with a “Process Cycle Efficiency” metric
When you first create a time value map you may be astonished at the levels of waste you find. One useful metric to create is what is known as “Process Cycle Efficiency” or PCE.
PCE is an extremely useful metric because it enables you to compare different services and processes against each other. Thus becoming another useful tool for determining focus and prioritisation.
You can also use PCE as a means of setting key performance indicators as they are simple to create and are directly related to customer value and costs to the business.
To create your PCE just divide the amount of value added time by the total cycle time of the process.
If we carried out 10 minutes of value added time in a 100 minutes our PCE would be 10%.
It’s not uncommon therefore to find that 90% of your activities add no value in the eyes of the customer!
Don’t panic though, according to the George Group, the industry average for PCE is 10% for service business processes and 5% for manufacturing so you may be above the industry average.
Fight the desire to implement quick data quality cleansing solutions
Upon seeing lots of defects and opportunities for improvement you may be keen to get your hands dirty and look at introducing data quality audit and cleansing processes to prevent downstream issues.
Stop and think about outright prevention instead. Why eliminate one wasteful activity only to introduce another cost base to the business?
Instead focus on long-term defect prevention by design data quality processes into the business service itself so mistakes cannot occur.