- October 7, 2024
- Posted by: Larry Walsh
- Category: Blogs
Channel data is meaningless unless all stakeholders agree in advance on what they’re measuring and how the intelligence will be used.
By Larry Walsh
The cliché that “data is the new oil” aptly captures the value businesses place on information. Companies seek data to uncover opportunities, validate ideas, and guide decision-making. With the right data, managers can mitigate risks and improve their chances of success. In essence, data is power.
However, few organizations truly possess the data they need — or, more precisely, they lack complete, accurate, and actionable data. This is particularly challenging within the channel.
Channel and partner teams, crucial components of larger vendor organizations, face significant challenges in accessing the data they need. Their sales, marketing, programs, and support operations are typically siloed and fragmented, and they often rely on other departments to obtain the data they need. This lack of direct access to data is a major hurdle they must overcome.
Additionally, many channel programs require partners to share their point-of-sale and customer data. Vendors are often surprisingly unaware of who buys and uses their products, relying on partners to provide the information needed to understand their end customers. Unsurprisingly, this data is frequently messy and incomplete due to the absence of common systems and standards. This underscores the urgent need for industry-wide standardization, a crucial step in ensuring the quality and reliability of data.
The core challenge isn’t just about data collection; it’s about the disparity between perception and reality. People tend to shape their beliefs around recent experiences or conversations, sometimes called “last person syndrome,” with the most recent opinion wielding undue influence. When data contradicts these ingrained perceptions, individuals are likely to question its credibility, dismiss it, or seek further evidence supporting their beliefs.
During the recent e2open Connect conference, I engaged with various channel practitioners, and they universally expressed the challenges of accessing quality data and convincing others within their organizations to trust that data. Several key themes emerged from these discussions:
- Data Accuracy and Integrity: Many participants raised concerns about obtaining clean, accurate, and consistent data. With data from disparate sources and systems, the lack of alignment and differing formats lead to discrepancies that erode trust and hinder decision-making.
- Partner Trust and Data Sharing: Organizations often struggle to gain access to partner data because of a lack of trust. Partners may be reluctant to share their data out of fear that vendors will interfere with their customer relationships. Transparent and reciprocal data-sharing agreements can help address this hesitation.
- Surrogate Metrics vs. Quality Data: There was widespread agreement that more data is not necessarily better. Several participants discussed the problem of relying on irrelevant or surrogate metrics that don’t lead to actionable insights. A focus on identifying the right metrics up front — and ensuring all teams agree on what those metrics mean — was seen as essential to resolving this issue.
- Operational Barriers: Growing organizations, particularly those with legacy systems, face the same internal data challenges that their partners do. Disparities between ERP systems, outdated processes, and manual data entry contribute to inconsistencies, making it difficult for all parties to collaborate effectively.
- Consequences of Poor Data: Without accurate, reliable data, companies lack visibility into where their products are landing and how they’re being used. This has serious implications for compliance, licensing, and software entitlements. Moreover, data inconsistencies can erode internal confidence, potentially leading to misaligned compensation and incentives.
The solution for channel organizations lies in developing holistic systems that collect, analyze, and report data from internal operations and external partners. However, success also depends on a shared understanding within the organization of what data is important and how it should be measured. Gathering large quantities of data is meaningless unless refined into actionable insights.
Channel leaders must prioritize identifying the key performance indicators that align with their company’s goals, ensuring data is collected and interpreted consistently. It’s equally important to secure agreement from all stakeholders about what the data represents and its significance for performance and outcomes.
Data is effective only if it has practical meaning. It’s valuable only when there’s clarity on how it will be used. And it’s useful for analysis and decision-making only when refined into actionable intelligence. Channel teams must do more to define their KPIs, justify the data they collect, and ensure all stakeholders understand these indicators. Without these conditions, data remains nothing more than a meaningless artifact.
Larry Walsh is the CEO, chief analyst, and founder of Channelnomics. He’s an expert on the development and execution of channel programs, disruptive sales models, and growth strategies for companies worldwide.