How Data Unveils Clues to the Solution
- Published: November 29, -0001
- Written by Nathaniel Palmer
If there were only one analytical technique the business process improvement (BPI) team could use, it should be quantitative data—and then I would expand quantitative data to include baseline data, customer data, and analytical data.
Baseline data is data that provides quantitative values to the measures for each of the two or three BPI improvement targets (goals) that the Process Owner specifies for the improvement project. This baseline data says how the process is performing today. It provides two clues towards process solutions.
- Should we even be working on this process? If the baseline data does not objectively prove that the process is critically underperforming, well, maybe this is not a process that really needs to be analyzed and improved.
- The baseline data gives the Process Owner quantitative values for how the process is currently performing; with this actual data he sets the goal values for the process once it is redesigned and implemented. Everyone will then know the size of the gap and the expectations for the future. If the expectations are large, there are implications for future budget investments in automation, technology, and major organizational or role changes. If the expectations are smaller, there are implications for less dramatic smaller changes that probably impacting fewer functions in the organization, and will be easier to implement.
By customer data, I mean voice of the customer data, e.g. from structured customer interviews, customer panels or focus groups, usability testing, going out and observing the customers in their work environment, and other methods. Customer data must be collected from the mouth of the customer and not assumed.
- Identifies what is valuable in the current process
- Clarifies the size of gaps from today to what is desired
- Suggests countermeasures to fix current problems from their perspective
- Identifies varying needs for different customer segments
- Requests functionality and services that are not in the current offering
- Hints at new possible products that are not even developed
Customers provide a wealth of information right from the ‘horse’s mouth’. The challenge for the BPI team is to figure out which are the critical elements and then figure out how to design for them and execute them.
Analytical data is a name I use for any data that helps to analyze the current process. It is quantitative data for any step, gateway, or sub process; it is data about inputs from internal and external suppliers, including the customer; it is data about time, waiting, and queuing; it is quantitative values to clarify root cause analysis (such as check sheets, Pareto charts and other reports); it is data about variation, and other types not specifically mentioned.
Analytical data helps the BPI team
- See where the big problems are in the current process
- Determine where clusters of problems are
- Find inefficiencies that appear in many areas
- Determine the leverage areas for root cause analysis and finding solutions
It may be difficult to gather real data about how the process works today. If the company has a BPM suite, then the suite can gather real time data from the current process. But otherwise the business process improvement (BPI) team will have to gather the data ‘manually’, by (1) looking at input forms for the last month and seeing how many were complete and accurate, what kinds of error categories there were or (2) time stamping transactions at each step in the process to determine times of steps and wait between steps or (3) noting where each process instance flows to identify the frequency of different paths, or (4) reviewing email requests, etc. Figure out how many data counts are needed to make a realistic assessment and get that many. No need to go back for 1000 transactions or for a whole year. Make the data revealing but not overwhelming.
With this information teams can see what areas to focus on in their process designs. They can determine if getting rid of problems early in the process will have the domino effect of eliminating problems later on so those problems don’t need to be tackled. Analytical data also provides language to create compelling stories of the current situation and later comparisons to tell of the extensive improvements.
Data is the best way to talk across levels. Most organizations have many hierarchal levels, and it is difficult for any employee or manager to talk more than two levels above them or below them because they do such different work and see the organization from different perspectives. But these conversations are possible with data. So get and use data to see what the situation is today, what the data says could be the situation in the future, and data to communicate in meaningful ways on many levels.
My new book, The BPI Blueprint: A Step-By-Step Guide to Making your Business Process Improvement Projects Simple, Structured, and Successful, was just published in February and is now available on Amazon.com