Case Study: HEMA franchise analyzes cash transactions

HEMA franchises are operated by some 110 independent retailers whose ability to adapt to the local market allows them to run their shops with extra care and attention. These retailers are united in HEMA’s franchise organization the Association of Affiliated Companies (AAC) which, among other things, works to discover ways to further improve shop efficiency.

The challenge

The deployment of business intelligence technology to optimize cost and revenue is becoming increasingly important in the retail sector. In this context, the need arose among the AAC management to register all the exceptions that take place at the checkouts, and in this way to increase discipline with respect to POS transactions within the stores. The information generated from an analysis of the daily transactions via the POS systems should reveal these exceptions. The AAC sought a platform to collect and analyze this information in order to use it as a basis for developing a strategy to improve efficiency in the organization.

This program is linked to the HEMA central server where all POS transactions are processed every night. All positive and negative exceptions per establishment that are above the national average are detected in this way.

AAC requirements

In November 2008, AAC initiated a process to select a solution to improve operational efficiency on the shop floor. A major factor in achieving this goal is the ability to identify losses and obtain insight into how products are scanned at the checkouts. Ultimately, the goal is for retailers to be able to better understand and control the full sales process.

ADT’s Sensormatic Analytics met all the technical requirements of AAC. Until then, this English language package had only been used in the United States. A precondition for AAC was that the package must be fully translated into Dutch. ADT agreed to this, and has also integrated specific HEMA terminology into the solution for the franchise organization.

The solution

AAC is the first in Europe to use the NaviStor module by ADT Sensormatic Analytics. This platform identifies conspicuous transactions based on benchmarking and trending.

At the core of Sensormatic Analytics is the ability to analyze large amounts of data and concisely present it as easily useable intelligence. By using Key Performance Indicators (KPIs) a retailer can for example sort, filter, order and score the data. In this way the software package makes it possible for ADT customers to quickly and simply identify critical areas of their operation that are in need of attention and improvement.

The NaviStor module also provides ADT customers with reports on exceptions that occur at the checkout. The system indicates, among others, positive as well as negative POS activities that require action, and it identifies checkout personnel that might need training. The system is able to e-mail reports on exceptions to the right people. ADT NaviStor also provides retailers with graphic information on shop trends per department and checkout employee. The NaviStor integrated data mining software package also makes it possible to quickly analyze data, isolate trends, and rapidly and accurately implement any operational measures necessary.

Starting on 1 September 2009, the first HEMA franchisees began analyzing POS data using NaviStor. Since then the package has been rolled out to all HEMA franchises. HEMA makes all of the POS data available. Every night, data from approximately 1,300 checkouts is processed via the package. This data is copied to the centralized application and then analyzed based on the KPIs. These KPIs are established in advance in consultation with the HEMA franchise organization. As a result, the software can for example analyze incorrect POS transactions, transactions with specific codes and return transactions.

This information is made available centrally, but processed locally. It is not the branch manager but the franchisee working locally who is responsible for analyzing the package. Each retailer has access to the information for his or her own locations.

To encourage the correct use of the solution all retailers attend a one-day training session. At the beginning of the day the theory on the capabilities of Sensormatic Analytics is covered. This is followed by practical training working with the tool itself. Because all HEMA terminology is included in the application, retailers easily recognize the terms. This contributes significantly to the ease of use, and has resulted in a short learning curve for the retailers.

Since the package is very extensive, a choice was made to make four different profiles available to retailers in phases. The AAC NaviStor test team, consisting of five retailers, tests each profile. After approval by the team, each profile is rolled out to the other retailers; gradually expanding the capabilities of the total package.


Since all POS transactions are inputs that can be recorded, it is possible to analyze them later. The analysis of this data resulted in a number of important findings. It appeared, for example, that the discipline of employees to use the correct product code, instead of a less useful alternative code, was much lower than expected. All HEMA articles contain a bar code and it was expected that virtually all articles would be properly scanned at the checkouts using this code. When the barcode is not recognizable, the barcode number can be typed in manually. In reality; however, HEMA found that in four to five percent of cases, employees opted to use the alternative code that registers the article only as a part of a product group. This alternative code is quicker but its use should be minimized because it undermines proper stock registration.

The system also makes it easy to see who performed specific POS transactions. This allowed the franchisees to provide individual training to those who needed it. AAC has also adjusted the POS training given to each new employee based on the NaviStor analysis results. A combination of these adjustments and individual training for employees who have been working at the store for a longer period, has allowed AAC to significantly increase discipline on the part of employees working at the checkout.

Because the number of errors made by employees is now substantially lower, structural points requiring improvement have become more obvious, and AAC has also been able to optimize its processes to increase total shop floor efficiency. Using NaviStor has also allowed AAC to identify and reward employees who respond positively, which has also increased employee satisfaction. Within three months AAC, with the help of Sensormatic Analytics, has succeeded in increasing discipline on the shop floor and implementing POS processes that provide better insight into this important part of the goods flow.

Why ADT?

The decisive reason for choosing ADT Sensormatic Analytics was the application of true, automated business intelligence to the POS processes. Sensormatic Analytics initially uses more than video images to detect and analyze exceptions in the POS process. The system also examines all POS data and applies modern analysis methods. ADT Sensormatic Analytics also provides graphical reports that make it easy for a retailer to identify and avoid exceptions. This process is much more accurate and efficient than other solutions on the market that try to detect exceptions based on video images alone.

In addition, after an exception is identified ADT Sensormatic Analytics is able to use the video images to further locate the cause; enabling the retailer to take preventative measures. In fact, several shops are conducting a pilot with video images fully linked to the POS data. This allows the corresponding video images for each transaction to be called up directly.

The confidence in ADT, built up over many years in other areas, also played a positive part in AAC’s decision to choose Sensormatic Analytics. The two parties are discussing ways to further expand their collaboration. An important theme is examining whether the analysis of the reports generated by NaviStor, which is currently being done by the franchisees themselves, can be taken over by a central team from ADT. ADT has a team of NaviStor experts that trains and assists retailers, keeps the KPIs up to date and modifies them when necessary to combat everchanging fraud strategies. This can further increase ease of use and efficiency.

Filed under Loss Prevention; Store PerformanceKeywords analytics; smart eas

Published on 2/12/2011 Permalink


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