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Client-Server Computing Explained in Brief

December 5, 2010 By Leave a Comment

Client-Server Computing is all around us.  By reading this web post you are experiencing client-server at work and there are countless examples and growing uses for client-server computing, especially as the popularity of cloud computing increases. So what is client-server and what are the differences between fat and thin clients?

Client-Server Computing leverages the capabilities of networking such as that used in your office, home, and the World Wide Web.  As the computing environment has evolved from mainframe systems with dumb terminals to a network of powerful desktop computers, corporations needed a way to take advantage of the computing power on both ends of the network, hence, client-server computing. By replacing mainframe systems which use dumb terminals, with a client-server architecture, a company can take advantage of the distributed computing power in the clients (the desktop PCs), rather than just using dumb terminals that require the server to do all the work.  Additionally, centralized data is still accessible to everyone who needs it.  It is a best of both worlds approach to computing.  The client-server model also offers unprecedented opportunity for growth, scalability, and concurrent multi-user access to central information.

Fat clients take the majority of the responsibility for the application logic, which frees the server from much of the work.  This approach has several advantages to the thin client approach.  Some of which are; a greater flexibility in application design and functionality, an increase system stability when updating application logic, and fat clients are generally easier to because they are client specific and do not have to be compatible with various client types as in a thin client system.

Thin clients, on the other hand, have little if any responsibility for application logic, which place most of the burden for the application on the server.  This provides several benefits distinct from the Fat Client system approach.  Updating the application logic is more easily accomplished since only the server needs to be updated.  Thin clients require less knowledge of the data on the server side, which contributes to a higher level of encapsulation and data integrity.  Thin clients are generally easier to debug and manage since the application logic is in a central location, the server.  Data management is also easier for the same reason.  Network bandwidth is less of an issue because most of the processing is performed on the server where the data resides rather than transferring data across the network to the client.  More robust applications and consistent performance from user to user, or “universally compatible” applications, are another advantage of using a thin client system.  

A client-server approach to a networked computer system provides a scalable and flexible system, which allows a company to maintain centrally accessible information, while at the same time taking advantage of the available distributed computing power that exists in the desktops throughout the company.   The client-server approach also improves the use of available computing power by separating functions and processes performed and delegating them to the appropriate and most capable machine.   

This idea of sharing resources across a network is location agnostic.  The user does not need to be aware of the how or where the process is being completed.  This encourages encapsulation of data, which also facilitates security, stability, and data integrity.

Filed Under: Data

Internet Security – Kerberos Protocol Explained

November 29, 2010 By Leave a Comment

The Kerberos protocol (named for the mythical guard dog of Hades) can defend against a variety of different security attacks.  The Kerberos protocol uses a system of tickets and authenticating applications to control access to network systems.  As messages are sent back and forth between the user, Kerberos, and the requested network services the messages are encrypted and there is always a piece of information missing from the message that only the receiver has.  This system makes these messages useless to anyone with malicious intent who may be eavesdropping on the network and trying to steal information or impersonate services. 

When a user wants access to a secured item on the network, they start the K-Init application to get a ticket-granting ticket.  The user enters their user name which is forwarded to Kerberos.  Kerberos cross references the user name and encrypts a message containing the user’s ticket-granting session ID with the user’s password.  This encrypted message prevents any rogue users from stealing a password in transit across the network.  The message is only unlocked if the user enters their password correctly in the K-Init application.

After the user unlocks the message sent by Kerberos, they are given a ticket-granting ticket and a session key.  If a user wants to access services, they send a message to Kerberos containing an authenticator message, the ticket-granting ticket, user name, user address, and the service being requested.  When the message authentication is confirmed, and the message is encrypted, the ticket-granting service gets a copy of the session ID share by the user.  Then the ticket-granting service makes a ticket for the requested service, determines a session ID between the service and the user, and then sends this message encrypted with the ticket-granting session ID that the user already received from Kerberos. 

This packet is encrypted with the session ID which only the ticket-granting service and the user have a copy.  This prevents the stealing of the tickets which authorize access to services. 

In order to prevent someone from impersonating a service and stealing information, the Kerberos protocol requires mutual authentication.  First, the authentication described above is used to authenticate the user to the service.  Before any information is sent to the requested service, the user machine waits from confirmation from the service.  The service sends a reply packet encrypted with the session ID which was granted by the ticket-granting service.  If a fake server receives these packets, it does not have the session ID and can’t properly encrypt a reply message.  If the user doesn’t receive the reply, no information is sent and the operation times out.

Filed Under: Data

Decision Making in Organizations

November 22, 2010 By Leave a Comment

Every day, countless decisions are made in organizations that impact corporate strategy.  In our work with Fortune 500 companies, we have seen decisions that range in effectiveness from brilliant to destroyers of value.  How can you ensure that your company’s decisions contribute to flawless execution and the advancement of the strategic plan?  We’ll use the example of a major health care company (fictionally named Health Tech) in financial difficulty that was evaluating a make vs. buy decision on a new software system and infrastructure.  Their existing system was blamed for inefficiencies, lack of flexibility, and ultimately loss of profits and market share that lead to its financial problems. As it turned out however, the root cause of the financial problems was ineffective decision making.     

Decision Making can be divided into Decision Management and Decision Control.  Decision Management is the process of initiating and implementing decisions.  Decision Control is the ratification and monitoring of decisions.  Different types of information are key to each of these, and in order to make effective decisions in organizations, proper assignment of both Decision Rights (the right or power to either manage or control a decision) and Decision Information (the pertinent  extrinsic and intrinsic data required to make a decision) are required. 

Decision Management requires information on the problem definition, and the potential solutions.  In our example, Health Tech’s leadership team required information on the capabilities of the current software, capabilities of the available software in the market, and the shortcomings of both with respect to the desired requirements.  Also, the Decision Makers would need to know the costs and implementation steps before presenting this information to the Decision Controllers for ratification. 

Decision Control requires information on the decision itself, such as the implementation steps, and how it will affect the company.  The effects include, the costs of the implementation, the potential failures, the various areas of the company that rely on the decision, and the intended results of each decision.  Those who are responsible for Decision Control must be able to judge each decision based on its application to the strategic business plan or “big picture”, considering both the company and the marketplace.  Additionally, the Decision Controllers must have sufficient information to monitor each decision’s performance in terms of cost and results.  For example, the Decision Controllers at Health Tech would need information on the estimated cost and time required to design and implement a custom software package before ratifying any decisions and the estimated cost and time required to modify an off the shelf solution.  Also, they would need metrics to continually monitor whether or not the new system, whether purchased or home grown, was effective after it was implemented.

Initially the symptoms pointed to a the software as the reason for the financial distress in the company, however, Health Tech’s financial problems were actually due to the poor assignment of Decision Rights within the organization.  More specifically, the problems were caused by the over assignment of Decision Rights and lack of control on Decision Making caused by Health Tech’s culture of entrepreneurship and rebellious empowerment.  Health Tech employees disliked the rigidity of health care regulatory agencies and they were empowered with both Decision Management and Decision Control. 

The assignment of Decision Rights at Health Tech was flawed.  First, the Decision Makers were not owners, and therefore could not be expected to make decisions that were in the best interest of the organization even if they had all the appropriate information.  Secondly, since the Decision Makers were not owners, they should have been assigned either Decision Management or Decision Control, not both.  Furthermore, the Decision Makers at Health Tech did not have the appropriate information needed to make the good decisions, partly because of the flawed computer system, which gave everyone misinformation and therefore blamed for the problems, and partly due to lack of communication throughout the organization.  Even the CEO did not have specific information about the severity of the problems because of the lack of communication

By separating Decision Making and Decision Control and correctly assigning Decision Rights throughout the organization, Health Tech would have had better information on the state of the company despite the errors in their software.  For example, they would have known that the computer system was giving the accounts payable department frequent problems.  Because with proper controls, billing and payables performance would have been one key metric in monitoring the effectiveness of the software application.  The Decision Controllers (presumably senior leadership) would be made aware of these flaws and could direct corrective action. 

However, Health Tech collectively did not know what problems existed or what to do about them because of a poor understanding of and lack of assignment of Decision Rights in the organization.   I would be remiss without noting that in addition to understand the basic components of Decision Making, communication horizontally across an organization (breaking down silos) is critical.  A properly designed organizational architecture is necessary to support the sharing of different pieces of information needed by Decision Management and Decision Control entities.  If this does not already exist, it will need to be created and then supported through a redesign of the organization.

Filed Under: Lead, Strategic Planning

You Are Never Too Old!

November 15, 2010 By Leave a Comment

 How many times have you thought to yourself, “If I had just …….”  Hindsight is just so much more insightful than foresight it seems.  When it comes to what we ‘coulda, shoulda, woulda’ have been, the good news is it is never too late to become what you want to be and we’re never too old to reinvent ourselves.

Just think of all the times you’ve heard inspiring stories of older people going back to school completing college degrees with kids younger than their grandchildren.  Recognizing that we can become something different, transform our businesses, or morph into something closer to our dreams is a particularly appropriate in these times of economic challenge.

I’m reminded of Betty White, the energetic much-older actress who continually gets new roles because she lives by this belief.  When asked, “When are you going to retire?”  Her response was, “When I’m no longer asked for.”  As long as we’re being asked for, we still have a passion for using our talents and striving to move forward…it’s never too late.

I want to thank my friend, Susan Brooks (http://www.servesyouright.net) for prompting this reminder.  I just finished reading her wonderfully positive book entitled, Serves You Right!, which is packed full of stories about how faux pas turned into successes, bloopers became bonuses and blushes of embarrassment were overcome by smiles.  While her messages focus primarily on customer service, I believe the same mantra is true of life in general.  What better time to echo this reminder than when so many feel so down and out.

I currently have clients who…

  • Have lost their businesses and are retooling themselves into new entrepreneurs
  • Have such slim margins they worry every day they might lose their business
  • Are in financial difficulty because of promises others made, but didn’t keep, legal concerns, or other misfortunes
  • Can’t get business financing because of the constraints of banks…and on and on and on.

By the same token, I have clients who are thriving in a wide variety of enterprises despite the economy.  What is inspiring about those that are the most stressed and worried is that they believe they aren’t too old, too tired, too stressed, too discouraged to reinvent themselves and survive and even thrive.  They are…

  • Reinvigorating their passion and breathing new life into their business
  • Taking an honest appraisal of their options and finding new creative sources of revenue
  • Finding non-traditional sources of funding and being more conservative in their growth strategy
  • Creating an entirely new line of products which service a different market…and on and on and on.

In all cases they are being rigorous in their discipline to create and use faithfully their strategy plans to guide and grow their businesses. 

Personally, I am seeing signs of growth and engagement of consulting services at a rate I haven’t seen for about 18 months.  As always, if we look for gloom and doom the skies will turn gray, and if we look for positive signs and possibilities we will find the sunshine. 

So what are you wishing you had done? What are you thinking you are too old to do?   What are you enduring in your business or your life in general that could be different, more positive, a fulfillment of your dreams?  Well, what do you choose to do about it?  Because, as the title says, you are never too old to become what you coulda, woulda, shoulda have been.  Assess.  Plan.  Go for it! 

Joyce Friel

Peak Performance Consulting, LLC 

11353 E. Raintree Drive

Scottsdale, AZ  85255

480 236 4266

www.peakperformancecorp.com

www.twitter.com

Filed Under: Lead

Retail Analytics: Competitive Differentiation Part 6

November 9, 2010 By Leave a Comment

Retail Intelligence

Retail Intelligence is comprised of four integrated solution groups:

  • Customer intelligence helps retailers identify, acquire, activate, serve and retain the most profitable customers.
  • Merchandise intelligence helps retailers drive revenue, protect margins and earn customer loyalty with optimized merchandise plans, assortments, pricing, promotions, space plans and allocations – all driven by unparalleled demand forecasting and predictive analytics.  
  • Operations intelligence lets retailers leverage organizational assets to trade with vendors and serve customers more efficiently and profitably.  
  • Performance management solutions provide the ability to analyze, forecast and maximize profits across the entire retail enterprise by monitoring cost and performance, helping retailers drive disparate functional units toward common goals.

The addition of the Ergenomics Power Index and other analytical services can then provide an additional layer of accuracy to this base. Advanced business intelligence can only be garnered by dedicating to a rigorous, enterprise-level approach to customer insight. Ergonomics’ Blueprint of Enterprise Analytics is a solution to help achieve and solve all that is solvable within an organizational paradigm.

info@ergenomics.com

http://www.ergenomics.com

About Ergenomics

Several things differentiate Ergenomics. Our commitment to an enterprise (not business or product-line) perspective is paramount in truly gaining intelligence that drives the entire company forwards—not just a certain product. Given this, our recommendations and results will provide a true and absolute baseline for executive leadership to compare numbers across the entire company (apples-to-apples, if you will).

Our staff may be one of the most experienced you will see—PhD economists and C-level business executives with top-rate support personnel to tailor a specific solution based on years of industry experience. And finally, we produce deliverables that will stand the test of time relative to their existence; not something that will be outdated after the initial run or implementation. Ergenomics will provide the client with true go-forward business intelligence.

Filed Under: Forecast, Lead

Retail Analytics: Competitive Differentiation Part 5

November 2, 2010 By Leave a Comment

Competitive Advantage Opportunity in Retail

Predictive analytics focused initiatives face a few obstacles. Many companies do not have a lot of experience in handling analytics projects which presents some unique opportunities for all involved (management, business line, vendors, etc). Often a key learning is to understand that analytics projects have a strong research and development component to them. Most organizations have a lot of experience and are comfortable with “execution” initiatives but may not be comfortable with “test and learn” process.

Also, selection of the right resources and partners can be a daunting task. Deploying enterprise level analytics that span business, statistics, and common sense can, at times, be a very foreign concept to an organization. First and foremost, the selected partners need to fit into the culture of the organization. They need to quickly come to understand the business problems and incorporate them into the statistical tools to solve the problem. In addition, the ability to clearly and effectively communicate recommendations is imperative. The Ergenomics approach for developing an enterprise-level analytical strategy for retail clients is rooted in the “decision tools” fundamentals of: Business Process, Data, and Analytics. A thorough understanding of these foundational organizational elements is critical to ensure an optimal business intelligence solution. Failure within—or lack of attention to—any of these interrelated components will result in an inefficient and underperforming result.

We define Business Process to incorporate such key items as a company’s overall business model, culture, competitive environment, leadership, business partners and resources, and realistic state of readiness. Similarly, within the Data perspective, we immerse ourselves in our client’s data elements, warehouse capabilities, legacy systems, ERP, and external or appended sources. Likewise, within Analytics, our team of professionals leverages years of academic and industry experience around target value, dependency, correlations, interactions, predictive impact, and significance. Implementation of standard industry leading analytical tools (SAS) can have a tremendous impact on business decision making. In addition, these tools can be modified to further enhance their effectiveness in understanding and analyzing an organization’s operational, customer, and financial situation.

info@ergenomics.com

http://www.ergenomics.com

About Ergenomics

Ergenomics vision and approach is to be innovative in the field of analytics. It is a holistic, enterprise wide philosophy that helps to keep us ahead of the competition. We also marry the power of seasoned retail executives with our PhD analysts to define and understand the problems and come up with solutions that work.

Our solutions are not simply theoretical; they are executable to help drive your business results. We are confident that we can help you leverage the power of analytics to improve your retail performance. Our fees are reasonable and built on the idea that we are only successful when you are.

Filed Under: Forecast, Lead

Retail Analytics: Competitive Differentiation Part 4

October 30, 2010 By Leave a Comment

Customer Driven Multi-Channel Marketing and Up-Sell and Cross-Sell Opportunities

Acquiring new customers is expensive for any retail business. Most of us are familiar with the Bain study that says it is five to seven times more expensive to acquire a new customer than it is to sell more to an existing customer. So if you are spending $1M on a mass promotion to generate $15M in sales, by focusing instead on selective customers built on our Ergenomics Power Index, you may be able to cut your ad spend in half and achieve the same sales results. This frees up more money for you to spend on other promotions, or simply drop to the bottom line.

The old Pareto rule is proven out time after time in retail. For most retailers, they will obtain approximately 70% of their sales from just 30% of their customers. Yet, most retailers spend their advertising equally against every customer. For most retailers, this means that they are likely spending more in advertising to these customers than they get back in sales.

At Ergenomics, we help you to segment your customers and model them so that we can create incremental sales dollars for you. We look at their shopping frequency, spending, and basket items to help you decide how and where to best spend promotional dollars most effectively.

Ergenomics has developed a Power Index that allows clients to understand how certain SKU’s, business lines, and customer segments truly impact profitability. That is, our approach and solution can drive business intelligence to a level that is simply not attainable otherwise. Our Power Index is a robust tool that helps you get all of the information you need quickly and efficiently. The foundation for developing this solution is in the calculation and application of the Power Index. This index has its roots in Game Theory and uses some of the algorithms inherent to this science. Recognizing that each retail customer is a player in their unique game enables the Principles of Game Theory. Game Theory states that if there is a game, there are rules, players, and groups. If a player wants to join the group, that player wants to gain positively from this alliance. For the group to let this player in, they need to benefit from the addition. Constantly changing rules are applied in a timely manner to the right game (retail customer needs), the right player (retail customer), and the right group (product offerings). A retail customer will not buy a product if the need is not recognized. A company will not sell unprofitable products to generate long-term losses.

info@ergenomics.com

http://www.ergenomics.com

About Ergenomics

Ergenomics is the first to apply the principals of Game Theory specifically to the activity of crossselling.

Affiliated partnership agreements with SAS, SAP, Teradata, and Accenture, among others, ensure world-class solution delivery for our clients. Our services include readiness assessments, business analysis, marketing optimization, data management, CRM analytics, customer insight, and risk management. Our ultimate goal is to enable organizations to implement advanced business intelligence and insights.

Filed Under: Forecast, Lead

Retail Analytics: Competitive Differentiation Part 3

October 27, 2010 By Leave a Comment

Demand Forecasting and Inventory Management

Some of the most successful retailers are using analytics for reducing stock outs at retail locations. Retailers are starting to understand how analytics can be leveraged to provide several quantifiable benefits: reduced stock outs, reduced inventory levels, optimized delivery schedules, and more efficient ordering process.

Inventory turn is a key metric in any retail business. The faster the goods move in and out, the more money an organization will make. Therefore, anything that can

“shorten the supply chain” or get rid of slow moving items will improve profits. Our goal is to help take the kinks out of your supply chain.

We have developed the Ergenomics Demand Forecasting Models which help you understand all of the different variables that are impacting your business. Many can be obvious while others are only detected through a sophisticated sifting and modeling of the data. For example, we have found in some instances that looking at the data over a 24 month period identified some key fraud issues that went undetected using the retailer’s 12 month analysis. This single analysis saved this retailer over $20M dollars in waste. From our experience, a 5% accuracy increase in forecasting for a $9b retailer will add another $60M in revenue. Our Ergenomics Demand Forecast Modeling leverages the power of both the latest technology and the analytical strength of our 10+ PhD economist analysts.

info@ergenomics.com

http://www.ergenomics.com

About Ergenomics:

Founded in 2008, Ergenomics is a private, boutique-style provider of enterprise-level solutions within the disciplines of analytics and technology services. Our focus is on data-driven business solutions that strengthen the relationship between a company and its existing customers. Our team consists of PhD economists, predictive analysis specialists, and senior business executives that deliver tailored solutions to improve the bottom line for customer centric companies in the areas of retention, cross-sell, attrition, risk management, profitability profiling, value enhancement, activation, marketing optimization, and loyalty.

Affiliated partnership agreements with SAS, SAP, Teradata, and Accenture, among others, ensure world-class solution delivery for our clients. Our services include readiness assessments, business analysis, marketing optimization, data management, CRM analytics, customer insight, and risk management. Our ultimate goal is to enable organizations to implement advanced business intelligence and insights.

Filed Under: Uncategorized

Retail Analytics: Competitive Differentiation Part 2

October 25, 2010 By Leave a Comment

Price Sensitivity 

  

One of the most common problems within the retail sector is pricing a product—not only initial pricing, but more importantly making the proper pricing decisions on an ongoing basis. Proper management of markdowns alone can contribute millions to a retailer’s bottom line. There are numerous similar products sitting on the shelves that are at different life stages and have complex interrelationships with other products and customers. Providing an optimal price of a SKU in order to extract maximum customer response is a challenge in itself. Virtually every retailer is running sales every week.

Usually each merchant looks at his or her business and decides what will be on sale. Yet the merchants typically do not know what customers will buy at full price and which will only buy on sale. If you could analyze the price sensitivity of each customer, you would find opportunities to significantly reduce your markdowns. Our Ergenomics Price Index is a unique method for modeling merchandise, customers and prices to help you index your customers’ price sensitivity. Some customers are so- called “cherry pickers” and will only buy an item when it is on sale. At the opposite end of the spectrum are non-price sensitive customers, who will just buy something because they want it or need it and do not care about the price.  Imagine the benefit of understanding price sensitivity at the individual customer level. What a powerful tool to use to reduce markdowns and to beat your competitors at the price game. 

We calculate the price elasticity for products and accessories that have extremely high or extremely low elasticity along with reasonable business impact (sales volume, margins, or life stage).  These accessories are picked for analysis. By using gross margins, we can come up with the best price change for such accessories.

Likewise, a basic market basket analysis can help find products that customers like to buy together. However, bundling needs to be evaluated for elasticity as well as likelihood of success before taking it to the customer. In order to increase the sale of some of the underperforming accessories, such accessories can be strategically bundled with highly elastic products. Similarly, a company will want to know the primary and secondary driver relationship qualities of each product (i.e., which product is the one that really makes people come to the stores). The gross margin of the bundle can be used for driving the price of the bundle.

info@ergenomics.com

http://www.ergenomics.com

Several things differentiate Ergenomics. Our commitment to an enterprise (not business or product-line) perspective is paramount in truly gaining intelligence that drives the entire company forwards—not just a certain product. Given this, our recommendations and results will provide a true and absolute baseline for executive leadership to compare numbers across the entire company (apples-to-apples, if you will).

Our staff may be one of the most experienced you will see—PhD economists and C-level business executives with top-rate support personnel to tailor a specific solution based on years of industry experience. And finally, we produce deliverables that will stand the test of time relative to their existence; not something that will be outdated after the initial run or implementation. Ergenomics will provide the client with true go-forward business intelligence.

Filed Under: Forecast, Lead

Leveraging Game Theory to Drive Growth

October 20, 2010 By Leave a Comment

Organic Growth : Cross-sell Expand To Existing ClientsThe most successful results for any company come from selling a broad array of applicable products to its existing clients. This provides the double benefit of meeting the ever-changing clients’ needs with the reduced acquisition cost incurred in selling to the existing clients. The challenge comes from the fact that each client has unique needs and objectives, and the client’s understanding and usage of any product is driven from these needs and objectives. The cornerstone to building a successful campaign is to increase product penetration and share of wallet needs to address all sides of this issue. The appropriateness of each offering is paramount. An understanding of the clients’ objectives—what factors drive the clients’ purchasing decisions— is vital. In addition, a complete understanding of the clients’ lifecycle determines whether the introduction of the product is critical. The potential influence upon the broader relationship with a financial advisor and the financial services company makes selecting the right product for the client at the right time the key to unlocking the real potential within any financial services arena. For most, this key has remained elusive. The recent turmoil in the financial industry has upset many clients to the point where the financial advisor needs to understand these criteria better than ever. Making the right proposals at the right time helps to overcome broad industry trends. Our key unlocks the door to this level of relationship, not only with a small and select portion of your business, but rather, with the entire relationship base across the entire enterprise.

To learn more about the Ergenomics Power Index and using Game Theory to drive retail sales, please visit our website or email us.

info@ergenomics.com

http://www.ergenomics.com

(612)245-4670

© ERGENOMICS 2009

Filed Under: Forecast
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