Process Shockwave
In traffic engineering, a shockwave refers to a change in the flow of traffic. A shockwave can be caused by an accident, merger, or rubbernecking to see a traffic stop. Steady-flowing traffic comes to a standstill and causes a bumper-to-bumper traffic jam. A shockwave can also flow in the opposite direction where cars “parked” in the middle of a highway start moving and traffic returns to steady flow.
Why Make Waves?
Status quo is comfortable and convenient. Several common sayings support keeping things as is:
- Don’t rock the boat.
- Leave well enough alone.
- The nail that stands up gets hammered down.
Change is hard. Effectuating major change in an organization requires a clarion call, specific knowledge, the right team, funding, and consistent stakeholder support. Plenty of excellent frameworks have been developed to strategically design and implement major changes including the Toyota Production System, Total Quality Management, Lean Six Sigma, balanced scorecard, strategy mapping, and many more. Yet, the advent of the information age and the coming AI revolution have introduced more complexity to life and work.
Process complexity, technical debt, and data quality issues further complicate the jobs of knowledge workers. Frederick Winslow Taylor, founder of scientific management, was a fierce advocate for identifying the “one best way” to manage business operations. In an organization, one may find that different operators — in spite of training and documented procedures — use different processes, IT systems, reports, etc., to complete a common task. Process harmony would be finding the “one best way” to perform a task. A process shockwave unlocks productivity and optimizes efficiency in an organization. Ultimately, process shockwaves leverage technology, Lean principles, and best practices to shorten critical paths, eliminate bottlenecks, and reduce process cycle times.
Highlights
At Happy Money, a fintech unicorn that provides consumer lending sourced from credit unions, I was able to create process shockwaves that substantially reduced the cycle times of major reporting activities. Here are a couple highlights from projects I lead:
Reduced financial ledger posting cycle time by 98% from 15 hours to 15 minutes by creating a Python automation algorithm leveraging Pandas, NumPy and Box API to prepare loan origination files for upload to NetSuite.
Developed a Python algorithm using Pandas, NumPy, and xlswriter libraries; pulled data from Salesforce loan system via Snowflake Connector API; resulting in a reduction of month-end investor reporting cycle time from 5 days to 20 minutes or a cycle time reduction of 99%.
Creating a process shockwave involves the following steps:
- Define the problem (Project Plan, SIPOC+ Diagram)
- Understand the process (Process Mapping)
- Do the math (Computational Analytics)
- Create data pipelines (Data Supermarket)
Take note, step 0 and part of every step is developing and validating a deep understanding of the needs, concerns, and pain points of the key stakeholders, end customer(s), and process participants. Ultimately, the customer needs a clear vision of what success looks like and a roadmap to logically get from A to B. Expect issues to arise, think 10 steps ahead, think like your customer and find answers to questions that they didn’t even think of yet.
Expect problems and eat them for breakfast.
Alfred A. Montepart
Process Mapping
A process is a series of steps that transforms inputs into outputs.
We can judge the effectiveness of a process based on metrics like cycle time or completion time, % defective products or components, number of repeated steps, customer satisfaction, or sales. I like to start new projects off with a one-page project plan with clearly defines milestones and a SIPOC +diagram.
A SIPOC+ diagram is a lean tool that lists out the suppliers, inputs, process (big 4-5 steps), outputs, and customers. The plus (+) includes the process boundaries (start/end), IT systems utilized, and measures of success (applied to grade the process outputs). I find it simpler to start from a SIPOC+ diagram and then work with process participants to define a more detailed process map or functional deployment flowchart with swim-lanes for teams, decision nodes, and more detailed steps.
Computational Analytics
In the example of month-end investor reporting, the monthly report consisted of 80+ data points pertaining to the status of a portfolio of loans owned by an investor. The detailed process involved a highly manual process of reconciling loan activity data (loan principal, payments, reversals, interest and principal paid to date amounts, etc.) against a Salesforce loan system and a Snowflake data warehouse. The logic from the manual process was reviewed, documented, and replicated in Python using the Pandas and NumPy libraries. There was a very detailed and iterative testing methodology employed to ensure and improve the accuracy of the Python model.
Service Value Stream Mapping
Lean Six Sigma is a meta framework first widely used by Motorola to improve quality, reduce costs, and reduce process variation. Lean Six Sigma combines decades of best practices from lean manufacturing, the Toyota Production System, Total Quality Management, Statistical Process Control, the teachings of Dr. W. Edwards Deming, and many more. Lean Six Sigma was initially used in manufacturing but later applied to service industries including financial services.
Value Stream Mapping (VSM) is a powerful tool used to analyze material processing steps. VSM helps lean practitioners to determine value added (VA) and nonvalue added (NVA) process steps as well as queueing, inspection, rework, and movement activities in the overall process.
Data Supermarket
Imagine that we are manufacturing bicycles. Process A in the value stream map below is where we put chains on partially assembled bicycles. The next step is inspection. Unfortunately, 50% of the bicycle chains are defective and pop after installation. Hence, we have a 50% rework rate because of the chains. Defective bikes are moved out of the process and placed in the scrap heap for potential rework. The plant manager plans to replace the bicycle chain supplier, but it will take 6 months. What can we do in the meantime?
In the meantime, we can create a supermarket at the Process A workstation. In essence, order and supply double the number of chains so that the rework rate goes down from 50% to 0% and subsequent movements (NVA or nonvalue added activities) are eliminated.
Data supermarkets can be created in process shockwaves that are very similar to the bicycle example. For example, some loans in a monthly report needed to be reconciled against the Salesforce loan system. Historical loan interest and principal payments needed to be researched and re-calculated in Excel. This analysis can take a substantial amount of time during the critical month-end investor reporting time period. I created data supermarkets to bring in data from Salesforce and Snowflake to quickly perform the financial reconciliation. This eliminated the need for manual inspection and rework. I also developed the Python algorithm to automatically correct errors in the month-end report.
In the final analysis, a process shockwave powered by Python, enterprise architecture knowledge, and Lean Six Sigma can radically transform your business. It takes a village to create the desired outcome — project identification, stakeholders, process participants, IT architects, software and data engineers, Python power users, and trainers. Everyone doesn’t need to be an expert to participate in the change ecosystem. Many companies have cultivated centers of excellence for continuous improvement and using process automation tools including Python, Knime, ServiceNow, Retool, etc. The key components exist in many organizations. Can your business benefit from creating process shockwaves?
