We have been involved in product configuration for more than 20 years, specializing in the automotive industry. Our IT specialists have been dealing with the challenge of configuring products and variants for several decades, and we have gotten to the heart of the problem of complex product configuration. R9 is our SaaS solution that handles complexity, performs efficiently and offers the incomparable flexibility of product combinatorics.
We aim to model the configuration of products in their full complexity and flexibility. Doing so helps our clients achieve real business agility in their product offerings. ZeroNtropy enables companies to manage customizable products and present them to their customers in an easy-to-understand way. Thus, ZeroNtropy contributes to the optimization of internal data landscapes, as well as to the creation of an experience economy for the customer.
With R9, the mapping of products becomes controllable, complete and unambiguous. What, how where, and to whom to sell a product can be determined explicitly without having to sacrifice complexity and variability. Product data is permanently stored at a central location and distributed appropriately. With R9, there is no need to discuss whether a product was or is sold in a certain configuration – it is unambiguous and formally defined. R9 completely deals with all variants, series, product lines and the corresponding prices over time: historically, now and in the future.
Markets and customer requirements are constantly changing. For many markets, it is crucial that a product range be adapted to emerging requirements very quickly. Successful companies are accustomed to recognizing customer needs, reacting to them with new offers or quickly adapting existing offers.
Along the value chain, companies have already greatly optimized processes and technologies. Modular product architectures take into account the trend towards increasing individualization. Development and production processes are able to reflect this constant change of customer requirements. However, one particularly evident obstacle of this trend is product data, which often lacks the necessary agility. A change in product data cannot always be implemented flexibly, as extensive effort is tied up in specification, implementation and testing, the consequence being that market entry of new and revised offers is delayed.
R9 is the solution to adapt product data flexibly. R9 addresses the product owners directly and gives them the ability to specify product characteristics and all offered variants both now and in advance of the next offer period. Software development teams can then build a frontend or online store based on the adapted product data and deploy it as release-on-demand functionality. Furthermore, all past offers can be traced. This may prove useful in the case of recalls, for example.
There are many configurators on the market. They all differ in process depth, offered features or product specialization. R9 has emerged from the trend towards individualization in a market that requires mass production as well as maximum possible variants. R9 provides an incomparable number of variants shown and meets the highest of performance requirements.
Decades of involvement in the optimization of configuration processes have led us to offer one of the most powerful configurators on the market. We pass the benefits of high performance on to our customers in the form of an extra degree of flexibility, which offers possibilities that are not available elsewhere on the market, especially for products with many variants or an extensive sales structure.
In addition, R9 offers a new dimension of performance to support a customer’s complex decision-making in real time. For the end customer, the goal is to achieve an experience economy, to have the desired product configured at that very moment, before their very eyes. Experience economy means to fulfill the customer’s request immediately and keep them engaged by offering an outstanding experience with the product and service, which already starts with the configuration.
Our service differs in its fundamental criteria: flexibility and variability of product offers, integration of customer contexts, handling the highest-possible number of product variants and delivering real-time offers.
Our configuration solution evolved from practical applications at large, globally-operating OEMs, and thus our implementation corresponds to real existing product data and use cases, backed by several decades of experience.
R9 holds and works with product data, rules and prices. It utilizes a flexible data model, so it can handle different product data from different industries, markets and companies. R9 adapts to the product data landscape of the specific customer and product.
R9 is designed for handling product data in the manufacturing industry, that is for tangible products, and for the trend towards a service economy around these products. The pure sale and ownership of a product is supplemented in a service economy by leasing options, financing, maintenance contracts and other additional business.
Different parts of a company differ in their perspective on the products they sell, so they use different systems to interact with their product data.
Product Data Systems (PDM) and Product Lifecycle Management (PLM) focus on engineering and production planning. PDM and PLM therefore do not target product sales, but require data for planning. Departments dealing with product sales require a different view of their product data. Products may be very much in need of explanation or oriented towards different markets through variants. Sales channels must be addressed individually to meet the individual characteristics of those channels, as is the case with private customers and business customers. PDM and PLM do not meet these requirements, especially with regard to sales-orientated features.
CRM systems have a strong customer focus, with a more indirect sales focus via importers and dealers, who also fall within the area of CRM systems. Their goal is to collect customer data along all touchpoints, involving everyone from prospects to loyal customers. Companies use this data to roll out optimized marketing measures with the goal of maximizing customer lifetime value (CLTV). CRM systems leverage historical customer data and contextual information, which are their strengths.
Their weaknesses lie in their limitations. They are limited in their ability to present products, their configuration options, the real utilization of contextual information, and – above all – performance.
Ultimately, any major complexity of variants, markets and the temporal variability of the product landscape overstrains CRM systems and prevents a complete representation in all dimensions.
ERP systems focus on order processing and can integrate warehouse management or connect to an MES system. Ideally, ERP delivers the availability of items, creates invoices, and takes care of open items and the receipt of payment, credit line, etc. ERP systems have no focus on product configuration and can often only display it provisionally. Typically, ERP systems require an exploded bill of materials.
R9 fills in the gap left by ERP, CRM, PDM/PLM and even portals and online stores, none of which fully handle and map configurable products.
The value that R9 can offer increases not only with the number of product features, configuration options, and restrictions in the configuration, but also with the number of sales partners, and the variance in sales partners or customer segments. Even if your product is less configurable than, say, a car, R9 proves useful if the configuration options vary greatly per channel, per market or segment. Furthermore, if your product data is very widely distributed in sales or you have high manual effort, in all cases it is worth using R9 to handle this complexity for you.
R9 is a self-service product, which is billed based on configuration packages. You can test it individually with real product data and integrate it into your own system landscape. Thus, using R9 also benefits startups hoping to quickly meet higher demands on their product configuration. R9 scales excellently. As requirements increase, R9 grows in every dimension to your individual needs. In terms of complexity, performance and support, R9 also meets the requirements of large enterprises. Deploying R9 is risk-free and future-proof.
R9 is a self-service product. Existing product data can be loaded or entered into R9. An online store can then load product data from R9. The complete integration service consists of providing data and connecting the R9 data interface to the online store. No further effort is required to map existing functionality and integrate R9.
When you introduce R9, your product data usually becomes clearer, formally more complete and freer of redundancy, mainly because the data is centralized.
R9 is offered as a SaaS product, so no separate IT infrastructure is needed. The option of a private cloud is also possible.
It is as easy to remove R9 as it is to integrate it. R9 can also be phased out at will by retrieving product data from a different source.
In any system, dealing with product data and rules always costs effort, but the introduction of R9 itself needs little effort. The system publishes all its data in interfaces and is completely transparent. An IT architect who knows the existing system landscape can use the system documentation to estimate and plan the effects on the system landscape without needing any help from ZeroNtropy. Above all, the outbound interface is relevant for estimating the impact on the existing selling systems.
It is not necessary that all selling systems immediately adopt this new flexibility in the product rules. The existing implementation with less flexible product data and rules can be converted step by step as needed. But even this step-by-step flexibility cannot be completely attributed to the introduction of R9. In mature system landscapes, it is almost always the case that a high delivery speed and the high pressure to deliver features lead to a state in which necessary flexibilities can be adopted later.
ZeroNtropy can also provide consulting services in this area, both from the perspective of the R9 product as well as from the perspective of the E2E architecture and product data structure in a company. We also consult on improving product data maintenance or maintenance processes.
For product data maintenance and protection, we have other software offerings that will be presented upon request. In general, securing product data quality is another process to be considered, especially if it exceeds a certain complexity.
The question of product data enrichment and preparation for sales is also a process that has to be considered with R9, because in the enterprise area there are cascading enrichments. These usually start in a PDM/PLM system and end with the configuration process for the end customer. A PDM/PLM system therefore remains the product data master while R9 loads and transmits the rules for configuration in sales. Content enrichment for presentation is done on the frontend or an authoring system.
However, this depends very much on the specific case. Many companies with completely outsourced manufacturing may not have a PDM/PLM, but only the extract from a PDM/PLM of the manufacturing company.
We know these issues in great detail and our experts can draw a roadmap for implementation.
Our product design for R9 stipulates that ZeroNtropy does not need to provide implementation support once the issues discussed here have been clarified. Even without a project and without consulting services, the product can be evaluated and connected simply through trial and error.
It is important to differentiate whether R9 will transfer all product data and rules at once or whether it will be introduced successively in small steps. Both scenarios are possible and can make sense.
As soon as R9 is rolled out more widely, the quality of the product data will increase. The product data is checked, optimized and improved with every integration, and redundancies are removed.
This has a positive effect on selling systems, because the scope for interpretation is no longer freely defined by the shopping system, but is interpreted by the developer. Thus, the product data that reaches the end customer is of higher quality. Fewer aborts mid-configuration lead to an increased conversion rate, and fewer configuration errors reduce the internal effort in reworking the system. Customer satisfaction is greatly increased when order processing is accelerated and when the product ordered is exactly the product delivered.
Overall, R9 greatly reduces the effort required for product data maintenance. Product management can begin to demand higher variability in the product data, and follow up on that within frontend systems. This is where real business agility begins, when short-term changes in product data or in the E2E configuration options are reflected immediately.
The impact of introducing R9 depends on the company structure, and – most importantly – it has to do with the creation of defined product rules.
The following areas will be influenced positively:
R9 directly affects product data maintenance because its focus is to define product rules comprehensively. The greatest effect on sales is that sales channels and markets or customer segments can be controlled sensibly. It is possible to allow a certain configuration in one market and not in another market because customer needs are different.
- Buildability check:
R9 can also check a product’s buildability with the maintained product rules. R9 can be called from a frontend or backend system to check the buildability of any configuration. This buildability check can be exactly matched to an existing buildability check in PDM/PLM, ERP or MES. It can also be set up differently. In fact, large industrial companies or other large corporations often have different tests for sales purposes and for actually buildable variants. There are many reasons for this, for example that customer behavior is different, that the costs of a completely free configuration grow exponentially with the number of variants, or for customs clearance, logistics costs, warehousing, etc.
In this context, it is important that R9 can ensure the buildability of a configuration and that only buildable orders are transferred to the backend with consequent application of the defined rules.
- Product Management:
R9 serves as a state-of-the-art tool for project management to define product configuration possibilities. As soon as all frontends learn to react variably to R9, product management gets far more possibilities for product customization. It will not make sense to define new variants all the time. But it can make sense in an end customer market to define new, more fixed variants for specific customer segments, as well as to market them for a few weeks and measure the sales results. In the long run, this flexibility of product configuration also means that the definition of product lines and the definition of products themselves can be changed easily. This eliminates many restrictions in the sales systems.
- Service and quality:
When there are clearly defined product data and rules, the error rate in orders remains low. With R9, it is possible to automatically check the ordered configuration for buildability before it is transferred to production.
R9 also offers a historical record of product data and rules and thus service employees can check exactly which configurations were possible when. In other words, R9 allows previously offered configurations to remain visible. A typical application of this is in warranty and guarantee cases, to see whether a product had a valid configuration at a certain point in time or independent of time, or whether the trade or the end customer had changed the product that invalidated the warranty.
Saving the exact configuration in previous orders is also very important in case of recalls or technical actions. A recall can incur immense costs, but the most important cost driver for recalls is the number of parts, which should be exactly determinable.
In the case of recalls and technical actions, a distinction must be made between critical and less critical issues that are resolved in the field during a service. Besides the actual reason for the recall, central topics include limiting damage to brand image and knowing exactly which products and which customers are affected.
In all these cases, knowledge of the exact configuration is crucial, not only the configuration in the accepted order, but also the configuration that was sold at that time.
The aim of R9 is to reliably define product rules, prices and – above all – configuration options and their validation. But R9 goes one step further because all of the above are also provided historically and in the future.
Historical means that for a customer with a long-running order pipeline, i.e. when products are ordered with a long lead time, R9 also allows a check to be made at any later point. This is especially necessary for complex industrial products. For example, if the order is placed six months before production, R9 allows you to check whether the configuration at the time of ordering was and is still valid.
This also works for future purchase orders, because you can determine and check whether configuration options will be valid in the future.
Furthermore, IT support goes a decisive step further because a development environment can also be tested for a future state. With R9 as its backend, an online store gets the possibility to access future configuration statuses during the development of new program increments. With the possibility to access prices and configuration options in three weeks or three months, R9 offers the ability to also develop and test on this status. This approach provides a previously missing step in business agility and generates real time-to-market capability combined with high-quality software delivery.
The unique selling point of R9 is that the most diverse domains and contextual information are linked in the form of product rules, and can be accessed in real-time despite a high number of variants. Product catalogs in legacy systems or in ERP/CRM/PLM cannot handle variability, real-time capability, or variant diversity, or even all of the above.
R9 serves as the central administration of the products sold. R9 integrates all product information, completely and accurately in a centralized fashion, and for all variants and characteristics. R9 manages all data about how the product can be configured and sold. R9 includes the product properties and their rules with combinatorics and prices.
R9 is the data master for all selling systems, for products, configurations and pricing. R9 offers neither content, marketing text nor visualization to the sales portals and consuming systems, because these differ from product to product, from branch to branch and from company to company.
The focus of R9 is processes. It provides a complete solution space for configuration, pricing and ensuring buildability.
Few conditions limit the use of R9 because it is implemented as a self-service application. The standard solution is execution in a public cloud. The application is accessed and configured in the browser. This requires a subscription with creation of login data for each business partner. All common browsers can be used for this.
Manual loading of product data and rules is done in the administration interface or is automated. Access data can be entered for the automatic retrieval of product data and rules. Common JSON files are provided for this purpose.
The data connection of the calling systems must be available and designed for high performance access. ZeroNtropy technically ensures international availability. If necessary, legal restrictions must be evaluated on a country-by-country basis.
For private-cloud execution, an AWS-like environment is necessary, which ZeroNtropy offers on demand. We can also implement other customer-specific on request. Many other product offers or service offerings are available upon request.
We will gladly answer any further questions.