These complex relationships are only exacerbated by dynamic geographic and cross-channel coordination requirements and multiple products and customer accounts. No industry is immune from these challenges. Companies that want to deliver the best experience to their stakeholders need to provide a complete picture of all parties in the relationship at the point of service. The ability to do this requires that organizations have a complete understanding of the complicated hierarchies and relationships that exist between them and their stakeholders.
This expanded view, referred to as organizational hierarchy management, helps companies clearly and consistently understand how their affiliates, business divisions and contacts in a single enterprise fit within a broader, multidimensional, global context. Advanced organizational hierarchy management approaches can help organizations track when people change jobs within and between companies, which can provide companies with new sales opportunities with a previous customer in their new job. Advanced systems can also identify these individual's replacement, which helps to ensure smooth transition for existing accounts. Companies that solve organizational hierarchy management challenges and place stakeholders into a wider hierarchical context will realize a broad range of business benefits, including:
- Better customer experiences, leading to increased loyalty and top-line growth,
- Enhanced financial reporting and more accurate revenue tracking,
- Additional cross-sell, up-sell and retention opportunities,
- Increased field productivity and sales targeting,
- More efficient sales territory and partner program management,
- Improved compliance management, and
- More effective risk evaluation and mitigation.
Real-World Application of Customer Hierarchies
The ability to place stakeholders within hierarchical context is invaluable to helping companies optimize business processes, enhance customer relationships and achieve enterprise-wide objectives. Organizations armed with the understandings that hierarchical context provides can improve revenues, decrease costs, meet compliance requirements, mitigate risk and realize many other benefits.
For example, a company without a hierarchical context to customer information could be unknowingly dealing with multiple customers who are, in fact, subsidiaries of the same enterprise, causing the company to inadvertently misrepresent its customer base and market presence. Understanding the hierarchical context of an individual customer may allow a company to identify areas of that customer's organization that it is not doing business with today - perhaps other locations or other subsidiaries of the organization. Conversely, an organization may fail to treat certain customers strategically because the organization is unaware of how much business they are actually doing with that customer and their related subsidiaries and divisions. All of this information can be advantageous to companies when directing field activities to the most productive and qualified opportunities.
Businesses can also use hierarchy information to accurately match or anticipate revenue gains or ensure loyalty programs are properly administered. For example, with accurate hierarchy information and an aggregate view of end-user licensing positions and histories, a company can better project and increase new revenues. This same company can also use this information to assign sales territories and improve field productivity as well as improve the accuracy of revenue recognition and financial reporting. Additionally, organization hierarchy information can give full visibility into a company's partnerships and can be used to match partner enrollments to revenue in order to ensure partner performance points are properly allocated.
Shortcomings of Traditional Methods
Hierarchy management can make a profound difference in business efficiency and effectiveness. However, many organizations struggle with how to implement these capabilities.
Today, companies typically either:
- Develop their own organizational hierarchy management system in house,
- Send internally collected data to external data providers for processing, or
- Purchase organizational data and matching software with which to apply it.
The first approach, in-house development of a hierarchy management solution, has significant risk and is rarely ever the core competency of the company undertaking the effort. Developing a hierarchy management solution in house is extremely complex and requires a much greater investment of time and resources than, in most cases, companies originally project. The expertise required to achieve a successful implementation is often misunderstood and scoped incorrectly, which can result in reworks, overruns, workarounds and other common in-house development challenges.
Unfortunately, the approach of relying on external data providers such as D&B (Dun & Bradstreet) also yields limited success. While external providers offer reliable information, they only deliver part of the picture. For example, D&B provides data on approximately 50 percent of corporations worldwide, but only from a legal perspective and InfoUSA covers only small and medium-sized businesses (SMBs). Most companies need information presented from a variety of angles, not just from the limited view offered by these providers. To fill the gaps, businesses sometimes utilize data from multiple sources, an often costly proposition that tends to provide a patchwork of pieced together views, which still fail to reveal the entire picture.
There are also others problems with the external data provider method. Companies concerned with the security risks of placing corporate data beyond the corporate security perimeter may not want to send data to an external source. Time lags result when sending data and receiving results back from an outside firm which can cause information to become outdated over time and require repeated and frequent updates. Also, batch processing does not yield results in real time, which can eliminate the ability to leverage information for on-the-spot decision-making.
The final approach involves purchasing data and a matching engine from a third-party vendor. This approach may help companies maintain tighter control over data, but it only provides a single, limited view based on the third-party's data. The same data degradation and latency problems of data from external providers apply to this approach. Moreover, it is very difficult to accurately match and correlate customer records across internal systems and data purchased from external sources. Other limitations of this approach include the high initial costs of data licenses, ongoing expenses to maintain current and consistent data, and the lack of scalability, accuracy, and performance required to match customers and place them in hierarchical context in real time.
