You are currently browsing the category archive for the ‘Sales Performance Management (SPM)’ category.
There’s a long history of companies not paying close enough attention to the contractual elements of acquiring software. Today, this extends into the world of cloud computing. Many companies are choosing to acquire software services through cloud-based providers and increasingly rely on access to cloud-based data, as is shown by our forthcoming benchmark research, in which a large majority of participating companies said that having access to data in the cloud is important or very important. As they say, I’m not a lawyer and I don’t play one on television, so what follows is intended to be nothing more than a conversation starter with legal counsel. But I do advise companies on how to use software to improve their business performance and provide guidance on what software they need to achieve their objectives. From that perspective, let me offer this blanket recommendation: Your company should examine the terms and conditions of its contracts carefully to be certain that it has the ability to control, access and retain its data in single or multitenant cloud-based systems. It should be prepared to add terms and conditions to any software-as-a-service (SaaS) contract to preserve ownership of and access to the data as well as other proprietary elements of that business relationship.
The fact is that choosing a cloud-based option presents a different set of legal issues that purchasers do not face with on-premises software, so it’s important that they consider the terms and conditions of the contract. Some of these issues aren’t completely new – they go back to the days before perpetual contracts and “open systems” were the norm. In that era, a company could find itself hostage to a vendor that shut down the company’s system remotely and prevented it from using the technology to run its business and retrieving its data from the system. Before entering into any SaaS contract or renewal, it’s important to review the details of the contract and its terms and conditions. The company should insist on modifying the wording of the contract if necessary to the satisfaction of both parties. It’s essential to perform this review early on, when vendors are short-listed, not at signing. It’s also important to review and, if necessary, revise the contract before each renewal. Customers have leverage at renewal since the most expensive event in a subscription-based business is losing a customer.
There are many facets to a SaaS contract, including performance, reliability and security as well as data. My focus here is on the last item.
Going into a relationship with a SaaS vendor, it’s essential that the contract specify what data the customer owns, whether that ownership is shared with any other parties, including the SaaS provider, and how the customer can obtain its data from the vendor. A SaaS contract should delineate what data the customer will have the right to take at the time it terminates the contract. This should include its data in the database tables but also might cover data about its specific configuration of the application and data from the database logs that pertains to its use of the system. It also should specify the form and format for that data as well as the timing of when the customer will obtain that data (for example, how many hours or days from when the customer requests it), how often the customer will be provided with data (unlimited requests is preferable) and the charges for such data transfers. Creating a set of extraction reports that harvests all the data from the buyer company’s tables may be adequate, but then again it may not be sufficient. The contract also should address contingencies for change of control (that is, if the vendor is acquired by another company) and bankruptcy.
Having database table data and information about the database structure is useful in the process of moving from one cloud vendor to another. Migrating from one vendor to another almost always involves setting up the successor system before the previous vendor’s contract expires. Also, in the process of finding and selecting a new vendor, a company will find it necessary to provide information about its existing system and the data that’s in it. This should be part of the background information included in a request for proposal (RFP), which should include a section detailing how the implementation service provider will manage the migration. Clarifying this part of the process ought to be a part of the selection process, and getting the details of the migration in writing before selecting a vendor and implementation partner reduces the possibility of encountering a potentially time-consuming and expensive problem. The responses to the RFP can help the buyer craft the contract terms and conditions with the successor vendor and implementation partner.
How often the customer can transfer data from the system vendor’s system is important because it’s likely that a customer will need to do so multiple times. For example, in most cases it will need to extract the data from the current vendor’s system at least once before the contract terminates in order to begin the implementation process for the follow-on system. This will be necessary weeks if not months before the termination date, followed by additional data extracts from the old to the new system. Companies also should consider how to replicate the process of running the incumbent and new systems in parallel during a testing phase. There may be fewer potential “gotchas” in migrating from one cloud to another because there are no system configuration and other infrastructure issues with which to contend, but there still will be many process, business logic and configuration kinks to work through. Even after migration, a company may find it necessary to maintain its instances with the old vendor for legal or audit purposes for several years. Setting the parameters of pricing a decommissioned version in a contract is likely to save money down the road.
There’s also the related issue of data ownership. A contract with a SaaS provider should acknowledge that the customer is the sole owner of its data and lay out the ability of the service provider to access that data with the objective of ensuring that the data can be used only to provide services to the cloud customer. Also, the legal ramifications of connecting a company’s cloud system to other applications or an operational data store should be spelled out.
Data retention and third-party access should also be covered in the contract because during a civil, regulatory or criminal legal proceeding, the customer may be subject to electronic discovery. This involves the exchange of information from electronic systems in electronic format. Data identified as relevant by the attorneys involved in such a process is placed on legal hold, which means that it cannot be deleted or altered. Making this explicit in a SaaS contract may reduce the possibility of legal repercussions if, for example, the vendor inadvertently eliminates or alters data that is covered by a legal hold.
The physical location or locations where the customer company’s data is held, as well as any backup sites, ought to be included in the contract. This is important because of requirements by some countries (for example, the EU Data Protection Directive) that specify where data can or cannot be located and whether data transfers are permitted. The contract also should spell out how the customer company will be notified ahead of time if the locations where its data is stored will change.
It strikes me that we are still in the naïve stage of the cloud software revolution, but it’s time to imagine the worst that can happen. I recommend that SaaS vendor user groups focus on the contractual aspects of their relationship with vendor, especially with respect to their data. They can collectively engage their corporate counsels in crafting a set of desired contract terms and establishing best practices for ongoing access to data and for facilitating migration from that vendor’s environment when customers wish to make the move. They also should focus on how secure their position would be in the event of a corporate bankruptcy and on the change of control provisions (if any) should their vendor be acquired. For their part, I recommend that vendors develop their side of contracts to anticipate having to meet their customers’ demands for open access and control. Just as buyers forced vendors to adopt a more open systems approach two decades ago, SaaS customers are unlikely to want to find their data locked in. Developing a legal framework to handle unfortunate contingencies makes better sense than trying to deal with issues on an ad hoc treadmill.
Robert Kugel – SVP Research
Managing prices has always been an activity of keen interest to businesses, but it has become even more critical to do it well. Over the past decade many companies have found their ability to raise prices has been constrained by intense competition resulting from Internet commerce, global competition and other factors. One tool for dealing with this pressure is price and revenue optimization (PRO), an analytic methodology that calculates how demand varies at different price levels and then uses that algorithm to recommend prices that should optimally balance revenue and profit objectives. Computer-supported PRO began in earnest in the 1980s as the airline and hospitality industries adopted revenue management practices in efforts to maximize returns from less flexible travelers (such as people on business trips) while minimizing the unsold inventory by selling incremental seats on flights or nights in hotel rooms at discounted prices to more discretionary buyers (typically vacationers). Price and revenue optimization algorithms are designed to enable a company to achieve fatter profit margins than are possible with a monolithic pricing strategy. Using PRO, airlines and hotels catering mainly to less price-sensitive business travelers found they could match discounters’ fares and rates to fill available seats and rooms without having to forgo profits from their high-margin customers.
PRO has expanded into other industries as computing power and data storage become ever less expensive, as software vendors have improved their techniques and algorithms to deliver better results and as the software has grown increasingly user-friendly. While the concepts underlying all PRO software are the same, there are different categories in which it is customized to meet the needs of specific industries. Retailers in particular have requirements that are best met by using applications that manage markdowns.
At the heart of price and revenue optimization is the concept of demand-based pricing. As its name suggests, demand-based pricing is a method that sets a price that is controlled by the seller’s assessment of what the buyer is willing to pay, which in turn is based on an estimate of a good’s or a service’s perceived value to the buyer. Companies use demand-based pricing to optimize – rather than simply maximize – their pricing to achieve revenue and profitability objectives. It uses data to estimate where the prospective buyer sits on a demand curve and therefore how much the individual is likely to pay. In some respects this is similar to what happens daily in souks, bazaars and other markets in cultures that do not insist on set prices. However, software makes demand-based pricing practical in large businesses and facilitates its introduction in societies used to set pricing.
Advanced analytic applications – especially for price and revenue optimization – have been gaining ground in corporate management because they have demonstrated to work. Significantly, they have the ability to deliver results that are unobtainable otherwise. Such software can crunch through very large data sets rapidly, apply purpose-built algorithms and automate the repetitive mechanical steps needed to put decisions into action. It also ensures consistency and supports objectivity in how executives and managers make decisions. Price and revenue optimization applications have benefited as the cost and complexity of the computing resources needed to use them have declined.
The adoption of PRO software is part of a broader trend of using applications to support fact-based decisions that once depended on experience and hunches. However, our benchmark research on the Office of Finance finds that just 20 percent of companies use price optimization analytics extensively. Only one-third look at product profitability. We think that more of them should do both. Analytic applications can digest a considerable amount of data to segment markets into useful groupings, pinpoint correlations and divine trends, to name a few tasks necessary for pricing management. However, companies investigating PRO software should narrow their search to applications that are appropriate for their specific business. While some offerings have broader applicability than others, no software product now available performs well in every industry.
Retail businesses that have multiple outlets, especially those that deal in trend- or fashion-driven products, face unique price and revenue optimization challenges and this affects the design of pricing management applications aimed at retailers. Many of these businesses are self-service, exclusively so if they are Internet-based, so there is no face-to-face contact during the product selection process. Negotiating prices isn’t feasible in most multiple-outlet retail settings in developed economies because of cultural norms and the hazard of delegating these decisions to front-line staff in even a midsize company. Unlike business-to-business transactions that involve ongoing relationships with established products, most stores today know little about most of their customers, so there is no direct way of judging an individual’s price sensitivity for the specific purchase at hand. In other words, most of the elements that support PRO strategies in analytics used for other types of businesses aren’t available to multiple-outlet retailers.
Since they usually cannot gauge the price sensitivity of their customers, retailers take a different approach: Let the merchandise do the talking. Products that aren’t selling well are by definition overpriced in that market. Retailers have used markdowns as a crude tool of price optimization for a long time. Offering a 30 percent discount near the end of the season is usually better than having to take a 60 percent haircut from a close-out specialist. Yet deciding when and by how much to reduce prices and then implementing the reductions at the store level in an optimal fashion is complicated because of the number of variables that must be considered. There are different types of merchandise, including long-life categories of goods that can be offered for sale for years, short-life fashion and fad items that are offered only once and those somewhere in between. There are differences in demand patterns and price sensitivity between regions and even at the store level. Seasonality, weather and movable holidays such as Easter and Thanksgiving must be considered.
Using analytic applications is superior to relying on experience and intuition because applications often demonstrate that the best decisions go against the grain of established practices. For example, retailers have found that smaller markdowns applied earlier and more frequently produce better results (that is, greater volumes sold at a lower aggregate markdown) than the common practice of making one or two big moves. Until the data became available, minimizing the number of markdowns was reasonable because of the cost in staff time to change prices at the store level. However, retailers using smaller and more frequent markdowns more than pay for these costs and then establish processes to facilitate price changes. Some retailers have found to their surprise that early small markdowns reduce the overall cost of markdowns. Analytic applications also are able to deal with a range of variables that retailers can use in markdown management. For example, they can vary percentages and frequency by size and color as well as by location. The software can monitor sales and inventory levels by the SKU at each store and automatically make detailed recommendations on how to adjust pricing. The software also enables retailers with multichannel operations (usually an online presence) to manage pricing decisions optimally across different types of outlets.
PRO software designed for markdown management also enhances the ability of a multiple-outlet retailers to run their business in a way that maximizes the productivity of their stores measured in sales or gross margin per square foot (or meter) or per linear foot (or meter) of shelf space. Items taking up space in a store or on a shelf have an opportunity cost in that they could be replaced by faster-moving or more profitable goods. Modeling the cost of the uplift required to free up space can result in a more attractive mix of merchandise that will improve returns.
While usability and capability of markdown management software have been improving, retailers face internal challenges in being able to utilize it. Analytic applications are only as good as the data available to feed the systems. Our research consistently finds that data accuracy and availability are significant challenges that almost all midsize and large companies face. Using markdown management software successfully also involves a change management effort requiring heavy involvement by senior management to endorse changes in how the organization handles day-to-day business as well as changes to processes and training and considerable amounts of follow-up to ensure compliance with the new ways of doing business.
Information technology is playing an increasingly important role in how companies conduct their businesses. Analytic applications can transform how entire industries operate. Today, airline and hospitality businesses operate very differently from how they ran in the 1980s because of the Internet and analytics. All sorts of businesses are finding that price and revenue optimization software enables them to improve their results measurably. Retailers should look into markdown management software as a way to fatten their bottom line. Other types of businesses also should consider PRO tools as applied to their particular needs.
Robert Kugel – SVP Research