Zilliant, a data-driven price management software provider, has developed a pricing suite for enterprises based on the vendor's proprietary, science-based Precision Price SegmentationTM and Dynamic Data AggregationTM (DDA). To learn more about Zilliant and its offerings, please see What if Companies Could Use Science to Align Prices to Market and Maximize Margins? and How One Vendor Parlays Price Variation into Profit Improvement Opportunities.
Zilliant Precision Pricing Suite (ZPPS) combines proprietary pricing science with analytics and workflow automation to support the pricing process continuously throughout the four sales phases: price segmentation, price analysis or sensing, price setting and optimization, and price execution. Each application within ZPPS has been developed to address one or more aspects of the data-driven model. Although the applications are tightly integrated with one another, they are deployed one at a time, and in the sequence best suited for the particular needs and objectives of each customer.
ZPPS applications offer a variety of role-specific interfaces designed to support all key pricing decision makers, including executives and marketing, pricing operations, and sales personnel. Interactive pricing workbenches are provided to supply the necessary drilldown and ad hoc query capabilities combined with user-defined reports and integrated visualizations. In a "different strokes for different folks" (personalized) manner, targeted reports, analytics dashboards, and alerts are provided to keep management well-informed, while scorecards and flexible hypertext markup language (HTML) interfaces provide sales teams with clearer guidance, information, and deal review process support.
Zilliant's Price Optimization and Management Applications
ZPPS science-based pricing applications for enterprises consist of ZPPS Server, ZPPS Analytics, ZPPS Optimization, ZPPS Price Manager, and ZPPS Deal Manager.
ZPPS Server acts as the suite's foundation, and this mandatory application collects data, organizes it, and allows it to be shared with the other applications. Given the need for extracting data from multiple transactional sources, ZPPS's service-oriented architecture (SOA) also enables an easier integration of pricing content directly into other enterprise systems. The relatively young age of the company and the product has had the benefit of being technologically modern, as it is based on Java 2 Enterprise Edition (J2EE) SOA concepts (see Architecture Evolution: From Mainframes to Service-oriented Architecture).
The suite is therefore modular in architecture to support the user enterprise as the user's pricing requirements and technical environment become more sophisticated. ZPPS's open standard technology is designed to work fairly seamlessly with the enterprise resource planning (ERP), customer relationship management (CRM), and database infrastructure the user company might already have in place to administer and calculate pricing.
To that end, ZPPS Server is the integration point for the application suite's incoming and outgoing data. Transactional and master data from CRM, ERP, and data warehouses are typical inputs. Outputs usually include price recommendations by way of price multipliers, policies, or pricing rules. These outputs are fed back into order management applications and pricing engines from, for example, SAP, Oracle (including Siebel), and others. The module propagates the resulting price segmentation model into all ZPPS applications, providing the applications with the more precise subset of market data relevant to operations, such as price indexing, peer grouping, key performance indicator (KPI) calculation, and price optimization.
ZPPS Analytics then drives pricing intelligence and decisions by providing insight through a series of template-based, customized views, and ad hoc querying to enable users (executives and managers) to measure margin, revenue, profitability, sales channel effectiveness, and discounting. Users are also able to measure price waterfalls, price bands, customer scatter plots, and outlier reports.
ZPPS Analytics is a decision support application that yields deeper insight into all price-related performance measures. The application creates a system of record for detailed profit and margin analysis to provide more precise comparative metrics and to identify latent opportunities for enhanced profitability. Underlying ZPPS Analytics is the multi-dimensional online analytical processing (OLAP) engine that leverages Microsoft Analytical Services (sitting on either Microsoft SQL Server or Oracle databases), thus combining scalability and performance with strong data security.
Featuring role-specific interfaces, each tailored to the needs of different business users and situations, ZPPS Analytics enables sales, marketing, and finance personnel to understand buying and selling behavior in greater detail. In addition to being a "pocket margin" system of record (see Know Thy Market Segment's Price Response), the module is a cross-functional management tool for identifying and resolving the most pressing ("top 10") profit improvement opportunities.
For instance, pricing analysts and other power users will typically access an interactive Analytical Workbench. This is a collection of pricing-specific analytical views that combines needed drilldown and ad hoc query capabilities with user-defined reports and integrated visualizations (such as profit bands, margin scatter plots, and price waterfalls).
Detailed Dashboards provide senior managers with holistic views of margin and profit performance, whereby the views range from an individual customer's or product line's contribution margin all the way up to overall company profitability.
Then, configurable Scorecards deliver deal- and customer-specific information to sales teams—whether online or disconnected from the system—to provide them with the decision support they need directly at the point of negotiation. A scorecard here is defined as a strategic, measurement-based management system that a company can use as a way to align business activities to its business strategy, and to monitor performance against strategic goals, for specific customers and channels, and distinct product markets over time.
Last but not least, Alerts push information, such as margin exceptions, out to all pertinent decision makers in real time, enabling them to proactively manage changes in market dynamics and customer behavior.
The idea behind ZPPS Analytics is to equip all power users with profitdriving answers to the following, often wondered-about questions:
- Who are our most and least profitable customers for product mix and cost-to-serve after accounting?
- How much is noncompliance with our pricing policies (such as free freight and extended payment terms) truly costing us?
- Which accounts are not living up to their purchase commitments?
- Which customer segments place the greatest value on our offerings?
- Where did our sales force discount below the price floors last month? How did this affect overall margins?
Pricing Optimization at the Core
The core and raison d'etre (purpose) of ZPPS has always been price optimization, even when the product was originally aimed at web-based pricing. The former Zilliant Pricing Suite (ZPS) Test and Monitor module helps measure market responsiveness to pricing, discounts, and promotions. As a monitor, it taps into transactional systems to discern market reactions to price movements in real time, whereby tests can be conducted by forcing price movements to get statistically valid samples. The resulting data can be used to interpolate how the market or specific segments will respond, since the product can unobtrusively monitor price quotations and orders as they occur, and thus record both wins and losses at each price point and at each price segment. Zilliant can then use this data to create price sensitivity curves in near real time.
In addition to delivering pricing insights, price monitoring enables companies to gain insights into other areas of their businesses quickly. Rather than relying on monthly extracts from Excel or some other tool after the books have been closed (as many companies still do today), one can monitor market price response in near real time. This gives companies a much quicker read on changing buying trends, competitive moves, customer's contractual compliance, and other key issues.
Price testing infuses controlled price variation into the market. Variation is necessary to create price sensitivity curves, and these in turn measure customer buying behavior across multiple price points. Although the products of some companies have natural variations in price (such as airline tickets, for example), testing can often gauge market reactions to targeted price changes in a more precise and systematic fashion.
In-market testing tends to be more accurate than focus groups and other traditional ways of gathering price sensitivity. The results of this type of testing are based on real customers making real buying decisions. Tests can also be created, deployed, and analyzed in much faster time frames than with traditional, off-line methods. In addition to testing discount levels and list prices, testing can also assess the effectiveness of different promotions, which enables companies to then use ZPPS Analytics to evaluate competing promotions prior to rollout.
Bundled with price testing and monitoring was the former ZPS Modeling engine, which uses a mathematical model to represent the user's business with all the unique influences on price, purchase, and customer decisions. Modeling describes the statistical process of defining a market or segment mathematically, and uses that mathematical model to predict future outcomes. Typically, models are defined and constructed by applying operational research (OR), statistics, data grouping, and algorithmic expressions. Further, a model is a representation of a set of components of a process, system, or subject area, generally developed for understanding, analysis, improvement, or replacement of the process. It is a representation of information, activities, relationships, and constraints.
The model performs forward prediction to determine recommendations and guidance on effective price or discount movements that need to take place. Such recommendations can help achieve margin, revenue, or volume improvements. In 2005, ZPS Modeling was renamed ZPPS Optimization to reflect the focus on maximizing margins for B2B environments, and the ZPPS Test and Monitor product was offered separately.
Even prior to the repackaging, ZPPS Optimization had evolved into an application that is well-suited for the discretionary negotiating environment that is prevalent throughout B2B manufacturing, distribution, and industrial services. Precision Price Segmentation and ZPPS Optimization work in concert to discern segment-specific price response patterns from price outcome data. These two applications then synthesize price recommendation guidelines (that is, the starting, target, and floor prices) for sales and marketing people that, when applied to negotiations, should maximize margins within and across all the different segments.
In other words, the ZPPS Optimization application enables companies to identify all possible differences in price response discernable from transactional and market data, and uses this insight to optimize prices. Such optimized prices, in turn, typically improve profits through two mechanisms: by setting price targets that more accurately align with each segment's demonstrated price sensitivity, and by translating these targets into precise, actionable negotiation guidelines that drive more profitable pricing decisions on each transaction.
Price Band Optimization Gets to the (Price) Point
ZPPS Optimization is designed to address many of the complexities of B2B price setting, including massive product portfolios, transactional data scarcity, build-to-order (BTO) product configuration, negotiation dynamics, long-term contracts, and a lack of detailed competitive market data. Zilliant's patent-pending Price Band Optimization approach determines the most precise prices possible based on available data. The application was devised to effectively set prices even with sparse, "win only" data from sales quotations or order systems (a common limitation in B2B), while continuously refining price recommendations as more data becomes available. The approach also has the additional benefit of being relatively easy to visualize, thereby empowering price analysts with the conceptual understanding they need to interpret results and take full advantage of the system.
To illustrate, ZPPS Optimization provides the optimized price recommendations as a deal envelope for each price segment, which is a set of three prices that provides comprehensive negotiation guidance. The envelope's upper bound is the start price, used as a rational stretch goal at the beginning a negotiation. Conversely, the lower bound, or floor price, represents the maximum discount that should be offered on a given transaction. Between these two is the target price, which reflects the optimal end point of the negotiation.
Providing price recommendations in the form of a deal envelope has been proven intuitive for sales people, and it supplies an appropriate balance of negotiation leeway and price discipline. Also, recommendations from ZPPS Optimization are produced in a format that is easy to integrate with transactional order management applications. Not only does this simplify technical deployment, but it also minimizes change management issues by supplying sales teams with optimized price recommendations within their existing and familiar quote-and-order applications.
Price policy and tactics are explicitly reflected in price recommendations, as the module exploits integer and goal-programming methods to determine the optimal balance between the user company's business objectives and external market forces. To that end, ZPPS Optimization can be configured to allow price managers to control the optimization model with goal-oriented business rules. In other words, administrative tools provide control over price policies and business rules that constrain the optimization model. These controls allow pricing managers to set policies and rules at the level of individual price segments.
In-line analytics and KPIs reveal the impact of new prices and policies upon margins and profits, and highlight specific price outputs that warrant additional review. The product also features dashboards that permit business users to review and adjust prices before deploying them into production. Managerial dashboards summarize the price recommendations and results produced by ZPPS Optimization, since these dashboards facilitate management review by showing the aggregate impact of price recommendations and sales negotiation compliance, and offer drill-through capabilities to underlying details.
The net effect of sales people complying with the optimized price recommendations is the tightening of the range of prices within each segment, and the shift of the overall distribution (for example, average price) to a higher level. That is how additional profits ultimately fall to the bottom line—a little at a time on every line item of every deal, as a tacit and invisible money machine. Having a well-designed price range in place for each transaction provides a user company with the ability to monitor and enforce price compliance at the actual point of negotiation (that is, within the sales representative's quoting and the sales execution system itself).
For example, a company may put a policy into place whereby sales representatives understand that discounting a product below the floor price requires additional approval from a manager or pricing analyst before the deal can be processed in the order management system. Likewise, sales representatives may be rewarded with additional commission for maintaining an average sales price at or above the target price. Conversely, sales representatives may be prevented from (or at least discouraged) from opening with prices above of the start price, as the transactional data has already shown that very few sales actually occur, and thus may put undue risk into the first round of negotiation.
To put this into perspective, a distributor user company now uses Zilliant to optimize over 10,000 quotes per day, with an average of 3 line items per quote. This means that over 30,000 prices per day are calculated and optimized throughout the full, end-to-end quoting and order management system with the help of ZPPS. This user now reportedly has over 6,000 identified price segments and associated deal envelopes, and the company credits ZPPS Optimization with its more than 15 percent margin profit increase. This user company's sales force has achieved an impressive compliance with recommended floor prices for over 80 percent of deals.
Prior to working with Zilliant, this distributor user company's approach to setting deal markups was highly discretionary. Sales representatives typically would only consider each customer's projected annual purchase amount when deciding what pricing to offer. In some cases, though, they would also consider product line margin targets, but these had minimal effects on final price outcomes due to the arbitrary determination of these targets.
In any case, if, for example, a user's sales organization already uses SAP or Oracle (including PeopleSoft or Siebel), Zilliant can integrate with these transactional systems, allowing the user company to incorporate advanced pricing guidance and analytics within existing systems, which will accelerate adoption by the user's sales folks. Most companies have deployed packaged quote and order management applications from vendors such as SAP or Oracle. Although these investments have improved the integrity and scalability of pricing administration, they have done little to enhance pricing intelligence and profitability. That is why many customers might want to integrate ZPPS with their order management applications: to create a holistic, data-driven system for price setting, execution, and fulfillment that unleashes the full power of pricing.
Pricing Optimization—Ultimately for Sales Forces to Strike the Best Deal
All of this optimization output can be, and has been, tied into a number of different interfaces, of which Zilliant's own ZPPS Deal Manager application is one option. ZPPS Deal Manager aims at helping sales personnel make better decisions on the spot by making it easier for them to distinguish a "good deal" from a "bad deal." The application empowers sales teams and pricing analysts with segment-specific KPIs, scenario comparison tools, in-line analytics, and optimized price recommendations. These features help sales teams to negotiate more profitable orders, agreements, and contracts.
By providing features for deal quoting, review, workflow, analysis, scoring, and enforcement, ZPPS Deal Manager also streamlines the deal review and approval processes, ensuring that each deal receives the appropriate amount of scrutiny. ZPPS Deal Manager also includes a set of rule-based features that enable the consistent use of pricing policies and business rules. This feature can be leveraged for the creation of price lists or to calculate prices at the time of quote or transaction.
Built to work with a wide range of agreement or contract types as well as to handle transaction and pricing exceptions, the Deal Manager module can (and it is often best to) work hand in hand with the other ZPPS applications, such as Optimization and Analytics, to achieve optimized pricing out in the field. Scoring KPIs not only take into account such margin drivers as discounts and other pricing variables, but also non-price factors such as freight, payment terms, product availability, and historical contract compliance. Ultimately, the sales representatives and pricing analysts can evaluate deals (at the line-item and overall level) in absolute terms, such as net and pocket margin, and also relative to each line item's peer group, as determined by price segmentation. One benefit is that bad deals no longer slip through unnoticed. Another is that more effective quoting and negotiations that will increase the margins of good deals, all while improving the efficiency and consistency of the associated processes, are encouraged. Finally, ZPPS Deal Manager enhances the customer relationship life cycle beyond initial negotiations via agreement compliance monitoring to follow-on orders and contract renewal support.
Like its brethren modules, ZPPS Deal Manager also leverages Zilliant's proprietary Precision Price Segmentation to score each deal against a micro-market of transactions within the same price segment. These "traffic light" KPIs and peer group price indices guide sales teams when pricing each quote. They also enable the module to recommend substitute products as an alternative to price concessions, as well as to cross-sell and up-sell items that should further improve deal profitability.
The available integration with ZPPS Optimization further refines ZPPS Deal Manager's pricing insight by leveraging Zilliant's proprietary Price Band Optimization to recommend the deal-specific negotiation envelopes comprising floor, target, and aspiration prices. Armed with this negotiation guidance and insight into associated commissions, sales teams should have the confidence and motivation to hold the line on prices and terms, thereby maximizing value capture on every deal. Sales and pricing managers can, in turn, rigorously evaluate proposed economics using detailed KPIs and analytics, such as price waterfalls and margin indexing. These managers can create and compare multiple deal scenarios to determine the best overall mix of products, prices, and terms. Furthermore, visibility into additional profit drivers such as rebates, payment terms, and shipping costs helps to highlight opportunities to maximize overall deal profitability.
In short, ZPPS Deal Manager empowers companies to maximize the profitability of every type of negotiated sales deal, including spot transactions, agreement orders, and long-term contracts, by supplying sales teams and pricing analysts with data-driven measures of deal attractiveness, real-time discount policy enforcement, agreement management, and automated deal-routing. The application's pricing guidance aims at enabling sales teams to spend less time researching discount guidelines and contractual commitments (often by manually shuffling piles of paper), and to spend more time selling value, and capturing it through effective negotiations. In addition, pricing analysts can more readily evaluate each quote against pricing policies without having to manually sort and plow through multiple spreadsheets or unwieldy price books.
Furthermore, ZPPS Deal Manager's intelligent deal queuing and routing (based on rules triggered by KPI scores) enable deal reviewers to focus on high-value deals that have the greatest impact on profitability. Automated approval for compliant deals decreases order-processing time and errors, and thereby improves customer responsiveness and decreases daily sales outstanding (DSO). Throughout this process, the application automatically creates a comprehensive audit trail that supports subsequent analysis and compliance reporting.
As an example, one Zilliant user once had 100 quote analysts to handle 30,000 quotes per month—worth over $300 million (USD). Today, 20 percent of these quotes are automatically approved via the ZPPS Deal Manager and ZPPS Optimization bundle, and the user company reports a whopping 96 percent price recommendation acceptance by customers. The product is used to handle price segmentation attributes both at the deal header and line level, with over $10 million (USD) of targeted profit impact for 2006, and with significantly improved average quote turnaround time too.
The most recent addition to the suite (and thus likely to have much room for improvement), ZPPS Price Manager, aims at helping pricing analysts and administrators to more wisely manage price lists and policies. With its integrated pricing analytics, planning tools, and scenario simulation capabilities, the application facilitates the alignment of prices with business goals, contractual constraints, cost factors, and other market dynamics. The idea here is to provide decision makers with a clearer, more comprehensive picture of the financial impact of pricing policy changes, thus enabling them to make more informed pricing decisions.
Important to note again is that all ZPPS applications were designed and built with Precision Price Segmentation as their scientific foundation. ZPPS Optimization leverages segment-level demand models; ZPPS Analytics leverages segment-level indexing and analysis; ZPPS Deal Manager works with segment-level KPIs and analysis; and ZPPS Price Manager works with segment-level price lists and policies.
This is the part three of the series What if Companies Could Use Science to Align Prices to Market and Maximize Margins?, which takes an in-depth look at the price management software provider, Zilliant, and its enterprise pricing solutions.
In the next part of this series, new developments in Zilliant's line of pricing solutions will be examined.