The Connection Between Six Sigma and CRM

Six Sigma is an industrial business strategy directed at improving the quality of process outputs by eliminating errors and system variables. The end objective is to achieve a state where 99.99966% of events are likely to be defect free. This would yield a statistical rating of Sigma 6 hence the name.

The process itself is thankfully more user-friendly. It presents a model for evaluating and improving customer relationships based on data provided by an automated customer relations management (CRM) system. However in the nature of human interaction we doubt the 99.99966% is practically achievable.

Six Sigma Fundamentals

The basic tenets of the business doctrine and the features that set off are generally accepted to be the following:

  1. Continuous improvement is essential for success
  1. Business processes can be measured and improved
  1. Top down commitment is fundamental to sustained improvement
  1. Claims of progress must be quantifiable and yield financial benefits
  1. Management must lead with enthusiasm and passion
  1. Verifiable data is a non-negotiable (no guessing)

Steps Towards the Goal

The five basic steps in Six Sigma are define the system, measure key aspects, analyse the relevant data, improve the method, and control the process to sustain improvements. There are a number of variations to this DMAIC model, however it serves the purpose of this article. To create a bridge across to customer relationships management let us assume our CRM data has thrown out a report that average service times in our fast food chicken outlets are as follows.

<2 Minutes 3 to 8 Minutes 9 to 10 Minutes >10 Minutes
45% 30% 20% 5%
Table: Servicing Tickets in Chippy?s Chicken Caf?s

Using DMAIC to unravel the reasons behind this might proceed as follows

  • Define the system in order to understand the process. How are customers prioritised up front, and does the back of store follow suit?
  • Break the system up into manageable process chunks. How long should each take on average? Where are bottlenecks most likely to occur?
  • Analyse the ticket servicing data by store, by time of day, by time of week and by season. Does the type of food ordered have a bearing?
  • Examine all these variables carefully. Should there for example be separate queues for fast and slower orders, are there some recipes needing rejigging
  • Set a goal of 90% of tickets serviced within 8 minutes. Monitor progress carefully. Relate this to individual store profitability. Provide recognition.

Conclusion

A symbiotic relation between CRM and a process improvement system can provide a powerful vehicle for evidencing customer care and providing feedback through measurable results. Denizon has contributed to many strategically important systems.?

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The Better Way of Applying Benford’s Law for Fraud Detection

Applying Benford’s Law on large collections of data is an effective way of detecting fraud. In this article, we?ll introduce you to Benford’s Law, talk about how auditors are employing it in fraud detection, and introduce you to a more effective way of integrating it into an IT solution.

Benford’s Law in a nutshell

Benford’s Law states that certain data sets – including certain accounting numbers – exhibit a non-uniform distribution of first digits. Simply put, if you gather all the first digits (e.g. 8 is the first digit of ?814 and 1 is the first digit of ?1768) of all the numbers that make up one of these data sets, the smallest digits will appear more frequently than the larger ones.

That is, according to Benford’s Law,

1 should comprise roughly 30.1% of all first digits;
2 should be 17.6%;
3 should be 12.5%;
4 should be 9.7%, and so on.

Notice that the 1s (ones) occur far more frequently than the rest. Those who are not familiar with Benford’s Law tend to assume that all digits should be distributed uniformly. So when fraudulent individuals tinker with accounting data, they may end up putting in more 9s or 8s than there actually should be.

Once an accounting data set is found to show a large deviation from this distribution, then auditors move in to make a closer inspection.

Benford’s Law spreadsheets and templates

Because Benford’s Law has been proven to be effective in discovering unnaturally-behaving data sets (such as those manipulated by fraudsters), many auditors have created simple software solutions that apply this law. Most of these solutions, owing to the fact that a large majority of accounting departments use spreadsheets, come in the form of spreadsheet templates.

You can easily find free downloadable spreadsheet templates that apply Benford’s Law as well as simple How-To articles that can help you to implement the law on your own existing spreadsheets. Just Google “Benford’s law template” or “Benford’s law spreadsheet”.

I suggest you try out some of them yourself to get a feel on how they work.

The problem with Benford’s Law when used on spreadsheets

There’s actually another reason why I wanted you to try those spreadsheet templates and How-To’s yourself. I wanted you to see how susceptible these solutions are to trivial errors. Whenever you work on these spreadsheet templates – or your own spreadsheets for that matter – when implementing Benford’s Law, you can commit mistakes when copy-pasting values, specifying ranges, entering formulas, and so on.

Furthermore, some of the data might be located in different spreadsheets, which can likewise by found in different departments and have to be emailed for consolidation. The departments who own this data will have to extract the needed data from their own spreadsheets, transfer them to another spreadsheet, and send them to the person in-charge of consolidation.

These activities can introduce errors as well. That’s why we think that, while Benford’s Law can be an effective tool for detecting fraud, spreadsheet-based working environments can taint the entire fraud detection process.

There?s actually a better IT solution where you can use Benford’s Law.

Why a server-based solution works better

In order to apply Benford’s Law more effectively, you need to use it in an environment that implements better controls than what spreadsheets can offer. What we propose is a server-based system.

In a server-based system, your data is placed in a secure database. People who want to input data or access existing data will have to go through access controls such as login procedures. These systems also have features that log access history so that you can trace who accessed which and when.

If Benford’s Law is integrated into such a system, there would be no need for any error-prone copy-pasting activities because all the data is stored in one place. Thus, fraud detection initiatives can be much faster and more reliable.

You can get more information on this site regarding the disadvantages of spreadsheets. We can also tell you more about the advantages of server application solutions.

Energy Cooperation Mechanisms in the EU

While the original mission of the European Union was to bring countries together to prevent future wars, this has spun out into a variety of other cooperative mechanisms its founders may never have dreamed of. Take energy for example, where the European Energy Directive puts energy cooperation mechanisms in place to help member states achieve the collective goal.

This inter-connectivity is essential because countries have different opportunities. For example, some may easily meet their renewable targets with an abundance of suitable rivers, while others may have a more regular supply of sunshine. To capitalise on these opportunities the EU created an internal energy market to make it easier for countries to work together and achieve their goals in cost-effective ways. The three major mechanisms are

  • Joint Projects
  • Statistical Transfers
  • Joint Support Schemes

Joint Projects

The simplest form is where two member states co-fund a power generation, heating or cooling scheme and share the benefits. This could be anything from a hydro project on their common border to co-developing bio-fuel technology. They do not necessarily share the benefits, but they do share the renewable energy credits that flow from it.

An EU country may also enter into a joint project with a non-EU nation, and claim a portion of the credit, provided the project generates electricity and this physically flows into the union.

Statistical Transfers

A statistical transfer occurs when one member state has an abundance of renewable energy opportunities such that it can readily meet its targets, and has surplus credits it wishes to exchange for cash. It ?sells? these through the EU accounting system to a country willing to pay for the assistance.

This aspect of the cooperative mechanism provides an incentive for member states to exceed their targets. It also controls costs, because the receiver has the opportunity to avoid more expensive capital outlays.

Joint Support Schemes

In the case of joint support schemes, two or more member countries combine efforts to encourage renewable energy / heating / cooling systems in their respective territories. This concept is not yet fully explored. It might for example include common feed-in tariffs / premiums or common certificate trading and quota systems.

Conclusion

A common thread runs through these three cooperative mechanisms and there are close interlinks. The question in ecoVaro?s mind is the extent to which the system will evolve from statistical support systems, towards full open engagement.

Web Analytics

There’s a vast ocean of raw customer data on the Web. Ever thought of the implications if somehow you could harness all that data and transform it into useful information? Information that perhaps you can use in your SEO (Search Engine Optimisation) and conversion optimisation?

There are web analytics tools you can employ for these purposes. But using web analytics tools will only win you half the battle. You’ll have to be proficient in configuring these tools to generate insightful and actionable results out of them. A poorly configured tool can produce confusing or even misleading information.

Our web analysts possess the expertise to configure and use web analytics tools, as well as analyse results and leverage information obtained from them.

These are the things we can do to help you take advantage of web analytics.

  • Discuss with your managers to establish your specific goals, to determine what specific data we have to collect/analyse and to plan out how to go about with the entire process.
  • Help you select an appropriate tool, install it and set optimal configurations including page tags, filters, funnels, reports and others.
  • Wield the full force of your analytics tool(s) to make sound business decisions.
  • Monitor the entire web analytics system and implement adjustments when needed.

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