Week 6

profileJaydee95
FlowchartImprovementProcessWk1.ppt

Flowchart Improvement Process

Overview

An “as is” shows the current logistics of a business process in a organization.

The process shows how business process works today.

An “as is” processes of sales department in a local organization will help us understand how the stakeholders routinely perform business

To understand the current state, interviews is among the common techniques used to collect information.

Analyzing business process helps business:

Minimize waste of resources

Clarify actual- operation step-by-step

Business analysts are able to ask the right questions.

Both current and future state are important because they help an organization become more client-focused.

An organization can adjust to meet its team needs..

*

Current State

Quotation

Customer agree to buy

End

Sign the contract

Stock?

Deliver soon after receiving payment

Deliver goods

Receipt of goods

After sales services

Prepare production

Arrange deposit

Yes

No

No

Yes

Process Improvement

  • The process of sales runs through various steps as indicated in the current flowchart.
  • Once a customer agrees to buy our products he/she signs a contract.
  • If the customer agrees to proceed with the process products are delivered after receiving the payment.
  • Goods are then delivered and receipts of goods issued.
  • Lastly after sales services such as transportation or discounts are extended to customers.
  • Process improvement is a process of identifying, analyzing as well as improving the current processes to meet new goals and objectives (Davenport, 2015).

Process improvement:

Define, measure, analyze, improve and control internal processes.

*

Future State

Business has remarkably transformed.

In the current environment consumers want a simplified process

Unlike in the current state, sales process should be simplified to minimize time and reduce cost.

Start

Look for a product

Did you find it?

Did you need it?

No

Yes

Forecast

  • Due to advancement in technology, it is essential to embrace technology in sales process (Taylor & Letham, 2018).
  • The current state is more of traditional and lengthy.
  • To eliminate delay, the future state should be made simple by eliminating various logistics such as manual processing of receipts.
  • From a judgmental forecasting, the future process will be efficient considering that it has minimized time and will reduce cost of operations.
  • Reduction in overall cost will increase the business profit margins.

Forecasting helps in taking proactive measures.

Helps to make logical decisions.

Helps to cut business costs.

*

Summary

  • Ultimately a process improvement process aims at improving results.
  • Apparently improving results is a challenging tasks for project managers.
  • As such, leaders needs a proven methodology to help accomplish set goals and objectives.
  • Using six Sigma roadmap managers are able to improve results.
  • The first step is to set the project up for success
  • Measure the current baseline for the process- data collection is necessary at this point.
  • Analyze the root cause of the problem- In regard to the bank time completion and costly process are the major problems.
  • Understanding what needs to change- Make the process more efficient.
  • Understand how to maintain the process- In this case it should be done through data collection and conducing surveys to understand customers feelings and satisfaction.
  • The ultimate goal of the improved process is to reduce the time the bank takes to process loan to book (Wang, Ashfaq & Fu, 2015).
  • The new process also hopes to increase efficiency
  • Reduce unnecessary costs

*

References

  • Wang, X. Z., Ashfaq, R. A. R., & Fu, A. M. (2015). Fuzziness based sample categorization for classifier performance improvement. Journal of Intelligent & Fuzzy Systems, 29(3), 1185-1196.
  • Davenport, T. H. (2015). Process management for knowledge work. In Handbook on Business Process Management 1 (pp. 17-35). Springer, Berlin, Heidelberg.
  • Taylor, S. J., & Letham, B. (2018). Forecasting at scale. The American Statistician, 72(1), 37-45.