We are currently experiencing a domino effect as IT manufacturers and other organizations, cut spending to offset revenue losses during these challenging economic times. Inevitably, during this belt-tightening process there have been major job losses across the IT industry, as sales of both hardware and software products significantly decrease. New technology service contract sales also face steep decline as a result of the reduction in IT spending. According to Gartner, Inc, The unprecedented decline of the global economy is impacting the IT industry with worldwide IT spending forecast to total $3.2 trillion in 2009, a 3.8 percent decline from 2008 revenue of nearly $3.4 trillion.
Regardless of this doom-and-gloom forecast, technology manufacturers and their channel partners can use this scenario to their advantage by shifting emphasis to service renewal sales and increasing their focus on warranty revenue streams. Now more than ever, is the time for this shift to take place because customer organizations are saving money by using their technology infrastructure products longer. This means the need to purchase extended service contracts to protect valuable IT assets is at an all-time high.
Data Quality Is Key
Data quality is the key component to a successful business. Complete and accurate customer records are essential for effective selling of products and services. It is important for a companys survival to establish and standardize data quality practices in order to maintain a healthy, progressive business during this economic slump. The impact data quality has on a companys sales effectiveness, and the systemic issues that poor data quality has on the entire organization can dramatically affect the sustainability of a business.
By utilizing the principles of data quality to improve business intelligence, companies can maximize service sales opportunities to ride out this economic storm while also setting their organizations up for success when the global economy recovers. Plus, with market research indicating growth in services revenue, taking a closer look at this business as a sustainable revenue stream clearly makes sense. Indeed, according to Gartner, worldwide IT services revenue totaled $806 billion in 2008, an 8.2 percent increase from 2007 revenue of $745 billion.
So how can organizations generate reliable and complete customer data in the interest of improving service sales? In order to solve data quality issues, its important to understand why the data got so disheveled in the first place.
Unreliable Data: Why Does It Get That Way?
Historically, services have been perceived as a one-time sale. The business intelligence obtained from a service sale (e.g., contract number, expiration dates and purchase order number) is often stored in a different system than product information and customer contact information. Hence, a data disconnect often emerges at the onset of the transaction. Another challenge impacting data quality issues is the fact that product and service registration often doesnt occur at all. Without registration, it is nearly impossible to align a service contract to the product that it serves, which subsequently affects a companys ability to renew that service contract when it expires. The data obtained from registration is critical for completing a customer record for follow-up renewal sales and future product refresh sales opportunities.
Another issue is that service contracts are often sold through a two-tiered channel consisting of a distributor/wholesaler and a dealer/value-added reseller, making sales processes complicated and leading to missing information in the collection of customer contract data. Challenges arise because adequate automated systems are not in place for properly registering or effectively tracking the sale of the service contract. In addition, data is stored in disparate systems, requiring time-intensive mining and management an undertaking that most companies would rather avoid. Compounding the issue, distributors work with hundreds or even thousands of VARs, who in turn may also represent numerous manufacturers, each with specific business rules and methods for registration. As a result, the quality of the registration data is compromised, which not only leads to delays in customer service entitlements but also hinders service sales and renewal efforts.
For these reasons, many companies have insufficient data to turn their services business into a successful profit center. It's not that the data doesn't exist; its that there are too few effective tools and processes in place to allow them to leverage the existing data. In addition, the cost to manually uncover and purse a service renewal opportunity is often perceived as too high. As a result, its estimated that most companies have at least five years worth of product and service contract data that they can turn into major revenue streams today. But because these same companies have been so focused on product sales, they have neglected this growing opportunity. Or, they simply have lacked the internal capability to improve the quality of their data and turn it into business intelligence that they can fully benefit from.
How Poor Data Quality Impacts Service Revenue Streams
Poor data quality is the primary factor driving these revenue detractors:
- More than 50 percent of maintenance contracts go un-renewed
- 30 to 60 percent of warranty service products are unregistered
- More than 50 percent of registration information is typically not actionable. Registration is defined as: complete customer contact information (i.e., phone, address, email, etc.), asset serial number, service contract number, purchase info, etc.
The Real Revenue Impact of Data Quality
A simple example illustrates how data quality is directly tied to service sales revenue. Lets say Company X sold 100 service contracts at $500 each for a total of $50,000 in revenue. On average, only 50 percent of those contracts get registered. Lack of registration translates into a lack of data and an inability to track contract expiration dates, which essentially cuts the opportunity for renewing those services in half, amounting to $25,000 in renewal revenue losses. And, industry standards suggest that only 33 percent of the service contracts that are registered will contain complete and accurate data to finish the renewal sale, resulting in $16,750 in actual renewal revenue. Do the math and youll see that Company X just lost $33,250 in revenue as a result of ineffective registration and poor data practices.
The cost of missed sales opportunities due to incomplete and poor quality data far outweighs the cost to improve existing registration processes and implement an automated system that ensures accurate and complete customer information. In a company without a technology solution or resources to improve registration practices, sales representatives are often burdened with the research and management of this data. And although highly motivated sales professionals may be willing to spend countless hours manually sifting through customer relationship management, enterprise resource planning and various reports that might be available to find potential renewal and new service sales opportunities for most, the time is not worth the effort.
With poor customer data available, its no wonder renewals are underserved and neglected. But the top-tier accounts that typically represent 20 percent of customers are never ignored. Why? Because of the high-dollar opportunities these deals represent. However, what doesnt get managed properly are the high-volume, lower-dollar opportunities that represent, on average almost 80 percent of a companys customer base equating to approximately 50 percent of a companys service revenue. But with each service sales opportunity bearing a perceptive cost and time-to-close investment, the need to pay better attention to associated data quality practices has simply not been a focus for most corporations in years past. Today, however, worsening economic conditions have prompted a new emphasis on service sales as organizations search for additional revenue to offset the loss of IT equipment and software sales.
The Steps to Economic Survival
Going back to the previous example, the revenue lost by Company X should hypothetically motivate its executives to examine existing data sources and processes for data capture to jump-start service sales. The process begins with gathering and assimilating important customer transaction information from ERP, CRM, point-of-sale, order processing and even legacy systems to create a single system of record of information. The data should include granular details, such as customer contact information, customer purchase order numbers, manufacturer sales order numbers, product serial numbers, service level information, service contract numbers and service expiration dates.
In a previous article, I addressed the principles of customer data integration and how companies are creating customer-centric data environments that blend together customer information from multiple data sources. (Unlocking the full potential of customer data integration. )
But to improve data quality, an evaluation of how data is captured and what exactly is being captured must be conducted. From there, procedures can be built for storing and leveraging that information. Today, a lot of emphasis is placed on technology solutions that provide automation tools to ensure data accuracy and completeness, right from the time of purchase. Automation takes choice and question out of the hands of sale representatives and provides them with quality leads that they can take action on. It also eliminates the research time once required to mine data for renewal opportunities. The automation process makes it easier for organizations to effectively deliver sales opportunities to sales personnel and then to transact those sales. With an automated solution, registration compliance can be achieved, with mechanisms in place for reaching out to customers to obtain the required data, and then store it in an organized fashion.
Making Automation Work: Know Your End Game
When there is reliance on data quality to maximize sales opportunities, technology solutions must be implemented to ensure data is accurate, complete and actionable. There are many low-cost technology tools available on the market today that can assist with the automatic registration process and improve the way customer and product information is captured and stored. But these solutions are only as good as the plan put in place for implementation.
To make an automated solution work efficiently, there must be an end game in mind. When planning and preparing data for automation, important questions must be asked:
- What purpose will the captured data serve?
- Who are the people in the organization designated to interact with the data (sales, marketing, IT)?
- What questions will the data answer in the future? For sales, key questions include: when are contracts coming up for renewal, and when does technology refresh make sense?
- When will the data present a sales opportunity? How much will it be worth?
Based on the answers to the above questions, decide what data to capture. If the goal is to improve service contract renewal sales, make sure end customer contact information (e-mail address, phone number, company name) has been validated and required details around product and services sold (hardware type, serial number, purchase order number, contract number) have been secured.
Once the goals are established, re-evaluate the existing process and improve the way data is captured. On average, only 40 percent of end customer information makes it back to the manufacturer. Much of this information can be obtained by requiring registration at the time of sale. Organizations should decide who will be responsible for capturing this BI and incent them. If the burden is put on the supply chain to ensure registration compliance, make sure there is a system in place to facilitate fast and easy product and service registration procedures.
The revenue impact of data quality is critical. You can start your company on the road to a better service business by evaluating the end game, keeping in mind the future actions required to leverage service sales opportunities. Use that understanding to review and improve the data capture process and to implement a system that ensures accuracy, completeness and integrity. By taking steps to improve data quality, IT manufacturers, OEMs and their channel partners can immediately take advantage of the annuity revenue stream available in services, while also setting themselves up for success when products sales rebound.
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