B.Ravi Sankar

AI is very well capable of interacting with customer and make them feel personal in each interaction by merging data, context and empathy at scale without crossing boundaries of trust. Better customer interactions with less customer efforts and high CSAT scores will definitely help the business expand
 
Customer’s expectation from any service are
·       Quick response on any queries raised
·       Receive accurate response on queries raised to avoid asking repeat questions
·       Faster query resolution with minimum interactions
·       Easy to interact with and have a sense of personal touch by letting them feel valued, heard and understood
·       Expect trust on data privacy
 
AI helps in better interaction with customer by:
·       Collecting the context with consent by pulling required data keeping in mind not using hidden data
·       Knowing customer better and in depth by building customer profile using data from past purchases, past interactions or support tickets, browsing history, etc
·       Use smart prompts for Bots that works on prefilling summary and also acknowledge earlier context showing respect and care
·       Feel customer valued by predicting needs and suggesting next steps that will help query resolution prior customer asks the question
·       Switch tone basis customer tonality and empathize basis sentiment analysis that reflects customer sentiment
 
For example, Account Payable Helpdesk is the function included in Procure to Pay process that handles queries from vendors, internal or external stakeholders related to invoices processed, payments done and PO created.
 
Below are few AI capabilities mentioned that can be used in AP Helpdesk across PTP:
·       Build AI Chatbots for automated query handling with 24/7 support and less repetitive tickets
·       Routes the ticket to required department basis query raised for faster and convenient resolution
·       Captures invoice data using OCR and NLP from documents or emails
·       Proactively inform vendors or required stakeholders on invoice status thereby reducing escalations
·       Resolve complex queries by searching policies, SOPs, etc using intelligent search & knowledge base
·       Adjust the tone basis customer’s response and urgency thereby building trust
·       Flags invalid invoices, duplicate payments thereby preventing financial losses

OEE, which is determined as the product of availability, performance rate, and quality rate, is a tool used to assess the real performance of a process.

Availability is the tool used to measure process performance by considering operating hours out of total available hours.

Performance Rate is the tool used to measure actual throughput against designed throughput.

Quality Rate is the tool that measures efficiency of products produced by considering good product output out of total product output.

Generally, benchmark of OEE for manufacturing sector is taken as 85% and all manufacturers try to achieve the best in class results

OEE calculations for a manufacturing process that yields finished goods at the needed throughput using the correct calculation methodology has been shown in table below. 

The following 5 scenarios show how quality is frequently measured inaccurately in order to unnaturally increase OEE for the process:
Scenario 1: Including reworked items in good products – In a few manufacturing processes, some of the rejected products are reworked to get a good product, and calculated those reworked items in good products.

Scenario 2: Finalize rejection % after audits that take a more time but consider rejection % into account beforehand.

Scenario 3: Reducing the customer specification limits to increase good product volume – Sometimes, process shift managers slightly reduce specification limit to get less rejection % compared to other shifts

Scenario 4: Considering rejection count only during stable production not during start ups – During production start-ups, rejection % is high as compared during stable production and so managers consider only rejection% while stable production

Scenario 5: Considering rejection % for the best production shift instead of monthly average or for the best operator instead of all operators
 

 
 

 

 
 

 

 

 

Overall Equipment Effectiveness (OEE) is a metric that measures the performance of a plant and depends on 3 factors that tells how efficient a plant is during the manufacturing process.
 
Overall Equipment Effectiveness (OEE) is measured as the product of availability, performance rate, and quality rate
where,
Availability is the parameter used to measure production or running hours out of total available hours.
 
Performance Rate is the parameter used to measure actual throughput out of designed throughput.
 
Quality Rate is the rate that measures good product output out of total product output.
 
An OEE of 85% is taken as benchmark in Manufacturing sector and try to improve the process to world class results
 
OEE calculations has been illustrated using right calculation methodology and also 4 scenarios has been illustrated where there are miscalculations in availability to inflate OEE for a manufacturing process that produces finished products as per required throughput.
 
Generally, availability is being mis-calculated to inflate OEE for the process and below are the following scenarios:
 
Scenario 1: Unplanned stoppage for raw material shortage not considered - Unplanned stoppage includes stoppages due to machine breakdown or other unplanned stoppages due to raw material stoppage or physical inventory audits, etc which are not considered in unplanned stoppages
 
Scenario 2: Planned maintenance not considered - Sometimes plant shutdowns due to maintenance are not included in availability calculations to inflate OEE no.s
 
Scenario 3: Break hours not considered - Sometimes operators take breaks in shifts due to which production is stopped and these break hours are not considered in availability calculations to inflate OEE no.s
 
Scenario 4: Planned maintenance and break hours are not considered to inflate OEE
 

 

 

 

 

 

Product Quantity Process Routing Matrix
 
PQPR matrix is a combination of the Product Quantity (PQ) analysis matrix & the Process Routing analysis (PR) matrix. It is used as a valuable tool to prioritize the focus of improvement efforts on building VSM for a range of products.
 
Product Quantity (PQ) analysis matrix is the tool that shows us to focus on the product family that contributes highest volume or highest revenue as compared to other product varieties in the organization and helps the lean manager to maximize the profits
 
Process Routing analysis (PR) matrix is the tool that helps to prioritize the product family having similar process steps and the manager’s take the decision on which product family to map first
 
Operations will be benefited by using PGPR matrix:
·       When a manager wishes to develop a VSM to optimize its manufacturing processes for a variety of items,
·       When a PGPR matrix can be prepared for the entire product range.
·       When PGPR matrix aids manager in deciding which product range to prioritize for creating VSM
·       When managers prioritize boosting the organization's margins
 
Example:
XYZ manufacturer produces only pain relief products in the form of balm, spray, liquid, gel, etc.
PQPR matrix 1 shows the list of pain relief products along with their sales volume and the processes followed in manufacturing. PQPR matrix 2 explains how products having similar processes are combined to a product family
 
With the help of PQPR matrix, lean manager takes the decision to focus on products of Product family no. 1 first since high sales volume % of 42% contribute’s to organization’s revenue and the manager builds VSM for Product family no. 1 first to improve the process thereby increasing the margins. Then, he gives the 2nd priority to Product family no. 2 and 3rd priority to Product family no. 3 for process improvement by building VSM
 

PDPC is one of seven management methods that systematically identifies possible issues or process flaws which can go wrong in process and seeks solutions to close these flaws.
 
PDPC tool is used for contingency planning in continuous improvement (CI) projects when:
·       In advance of a plan's implementation (Improve phase)
·       Used for preventing problems or providing better solutions for a problem
·       Deliver complex or complicated project
 
Create a PDPC using a tree diagram for a contingency plan that has 5 levels as shown below:
·       1st level – overall objective
·       2nd level – main activities to reach the objective
·       3rd level – tasks performed to get activities
·       4th level – possible risks while performing tasks (generally risks are identified by conducting brainstorming sessions with the team; Review risks and eliminate insignificant risks from 4th level
·       5th level – preventive actions (one or more) for each risk identified so that these risks can be prevented. Actions that are practically possible are identified and actions that are difficult for implementation due to cost constraints, more time taken, difficulty to achieve are not considered
 
I have used PDCA tool shown below for better improvement of invoice processing process. Green marked in Level 5 are the actions that can be taken and red marked those actions that cannot be taken
 
L1: Objective L2: Activities L3: Tasks L4: Risks L5: Action Plan