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we produce deliverables that will stand the test of time relative to their existence; not something that will be outdated after the initial run or implementation.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.

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.

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.

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.

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

 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.  Ergenomics is the first to apply the principals of Game Theory specifically to the activity of crossselling.  We have developed our Power Index to complete the science.

Three main differentiators result from our position:

1. We offer the only algorithm tailored to enterprise-wide cross-selling. Our Power Index allows our clients to identify on a per customer and per product level (i.e., what each customer is most likely to need, what each customer is most likely to buy, the ranking of all products by the propensity of each customer’s needs and wants);
2. Using our Power Index, we have the ability to show our clients the importance of each product and teach our clients to use this information to improve their customer relationships (i.e., how important is Product A to the overall relationship, what is the relative importance of all products against each other);
3. We also have the flexibility to apply our process to any natural segment. This science can be applied at the enterprise level, at the business line level, against customer segments, regionally, or at any other segmentation that the business needs this intelligence or sees potential ways to benefit from the analysis.

In our application, rules work both ways so that the desired effect is that the customer and company mutually win. The customers get appropriate offers, and the company sells and promotes the wining coalitions of profitable products.  The result is that even when product profitability does exist, figures can be grossly misleading for some products because of the intermingled nature of a retail relationship. Winning coalitions are defined when a product forms a winning mix if it adds to the sustainable profit of the mix while not sacrificing its own margin. When this condition holds true, the product is called a “swinger” and is therefore pivotal for a given mix. The definition above is used to derive the probability of a swinger product as the ratio of all relevant swinger product mixes to the total number of coalitions or permutations that include the product under consideration.  By calculating each Power Index we determine where each customer is in the completeness of his or her relationship with the company and identify the next products that should be offered to each client. The algorithm is not limited to one or two selected retail products, rather it applies across the entire spectrum of products and services. For each available product, the Power Index enables us to rank the priority of offerings.

info@ergenomics.com

http://www.ergenomics.com

(612)245-4670

© ERGENOMICS 2009

 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

(612)245-4670

© ERGENOMICS 2009

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.

In part 3, we’ll address how demand forecasting is leveraged to shorten the supply chain and improve profitability.

info@ergenomics.com

http://www.ergenomics.com

(612)245-4670

© ERGENOMICS 2009

Companies need to be flexible and reactive so they can quickly respond to increasingly sophisticated customer demands. Businesses must be able to change their business models so they can collect real-time business information and drive the efficiency of their day-to-day operations.

Several critical challenges confront today’s retailer: price sensitivity, demand forecasting and inventory management, customer driven up-sell and cross-sell, multi-channel marketing, and fraud detection and loss prevention; just to name a few. Ergenomics believes in the use of enterprise wide analytics to create one common view of the enterprise which enables everyone across the organization to approach the business with the same set of numbers and data.

Our analytics approach starts with improving your customer knowledge. Retailing today is about making the process of getting the right products to the right customer at the right price at the right time a scientific, predictable routine. The days of “stack it high and watch it fly” are gone. This means making your organization as efficient and effective as possible.

As they say, “retailing is detailing,” and the devil is in the detail. That is where the Ergenomics’ Blueprint of Enterprise Analytics allows us to sift through massive amounts of data quickly and precisely to help you identify and predict selling opportunities. We leverage tools like SAS and SAP to help our PhD economists assess your customer information and help build you a Customer Performance Dashboard along with other reports to help you leverage the power of customer data. Our approach to retail analytics is robust and straightforward. Ergenomics deploys expertise (technological, analytical, and business line) that can hone in on opportunities with an organization to maximize their customer portfolio. All areas of concern can be addressed and optimized through our disciplined and rigorous execution.

Business Process > Data Analytics > Assess > Build > Optimize > Support > Train > Deliver

Understanding the current customer’s buying pattern, price sensitivity, interdependence of product lines to each other, and each SKU’s true and absolute profit contribution not only produces immediate results, but can be modeled forward to gain efficiencies in future operational and marketing decisions.

In part 2, we’ll address the topic of price sensitivity.

info@ergenomics.com

http://www.ergenomics.com

(612)245-4670

© ERGENOMICS 2009

Forecasting helps to obtain a good comprehension of the observed data and accurate future predictions based on this comprehension. The main goal, however, is to assist executives with decisive information they absolutely need to make the best possible decisions. Acting on these recommendations can significantly aid in solving problems, gaining new opportunities, and ultimately better business management. Examples of possible uses of forecasting are to reach corporate goals, to plan external economic and competitor impacts, to improve inventory management, to improve customer service, and to increase profit margins.

Key elements in forecasting are Team and Framework. In this article, characteristics of both are mentioned.

A successful forecasting system starts with forming a good team. Essential team members are Business Analyst, Data Analyst, Project Manager, Statistician, and Solution Architect.  Roles and responsibilities each member contributes to organizational direction. Business Analyst makes sure credibility of the business information through careful research. Data Analyst automates historical file extracts, and optimizes the process time and accuracy. Project Manager has a unique position in forecasting projects, because of responsibility of asking details about the system and its sponsors. Statistician is responsible to find what is unknown, the forecasts, by studying the actual numbers and applying internal or external factors. Solution Architect works with system results as well as other available data to create a visualization tool for business leaders to make data driven decisions. With this team in place the following benefits could be expected; collecting business owner needs, and changes in the business, business approval of pre-published numbers, increased timeliness of business decisions, what-if scenarios implementation, short timeline delivery, easy to use custom solution interface, integration of major economic indicators and competitors market share, unnoticed real trends discovery, maximized profit margins opportunity, strategic business portfolio creation, on the spot tactical recommendations, centralized one version of truth, collaboration with other official numbers, automated step by step process, mitigation of known and unknown risks, and institutionalized ongoing maintenance.

The Framework for the forecasting system should include the following phases; Data Gathering, Information Gathering, Modeling, Reporting, and Recommendations. In the data gathering phase, historical data is extracted to be studied in order to gather historical data at the most granular level possible, input missing data points and attributes, structure hierarchy levels, and determine the business focus hierarchy level accuracy is tested. Information gathering phase follows what collected data is to note internal business circumstances, implement structural brake notifications, and detect anomalies and outliers. Modeling phase is where normalizing and transformation of data is taken in to account and studying the relationship between observed data and economic and competitor indicators. It this phase also models are estimated, validated, tested and selected to create forecasts. Reporting phase of the framework helps in both forecasts quality and applicable information selection such as static accuracy testing, dynamic best and worst performance analysis. Recommendation phase where Return On Investment are clearly observed because this phase tells business users where the potential goal gaps are, what resources to be added in business operation, and simply brings various departments to one table to list actionable items.

Some of the items need more emphasis;

• - Such as experienced statistician who has industry knowledge and built dynamic forecasting engines previously
• - The systems results needs to be reviewed regularly, this review includes business expected numbers and model numbers accuracy testing, what is working and what needs to be improved, model attributes
• - Constant Business and Forecasting Team communications
• - Selecting forecast engine tool for the corporate need and building a customized visualization tool for result comparisons such as actual to actual, goal to actual, forecast to goal

In conclusion, this article is about what is essential for a successful forecasting project. It is teamwork with applied framework. As long as these two are in place building, adjusting and maintenance of forecasts for the whole organization is an easy task. ForecastWare.com is built on this fundamental approach.

http://www.ForecastWare.com