4.2. Step 1: Identify Opportunities

The first step was to use the influence network data to assess TechFirm's current level of engagement with influential people and discover opportunities for strengthening relationships that could help the firm achieve its business goals. TechFirm wanted to increase new-customer acquisition in three sales regions, improve customer satisfaction, and shorten the sales cycle for deals currently in the pipeline in those regions.

Opportunities were identified by the following:

• Performing a gap analysis

• Segmenting what we call key network members (KNMs)

• Forming cross-functional teams responsible for developing a strategy for engaging each group of KNMs

Key network members, as the name suggests, are those who are in the best position (because of their relationships, the nature of their network, and their overall role in the network or a subgroup of the network) to support the achievement of business goals. They are identified through a series of algorithms that take into account both relationship dynamics and business impact.

4.2.1. Gap Analysis

We started by performing a simple gap analysis, comparing the list of KNMs identified through the influence network data to TechFirm's sales targeting list, the list of individuals the company used in marketing and communication efforts, and its own internally generated list of "influencers." We found that 65 percent of the KNMs identified through the network analysis were not on any TechFirm lists.

We then looked at the events that TechFirm had orchestrated during the previous year and compared the speakers and attendees to the list of KNMs. We also compared the list of KNMs to speakers or panelists lined up for events in the coming year. The purpose of this exercise was to assess TechFirm's level of engagement with the KNMs. We found that 78 percent of the KNMs had not participated in any TechFirm events (either as speakers or attendees). More important, we found that 84 percent of the speakers TechFirm had engaged in the previous year were not mentioned by a single person as someone whose opinion was trusted or whose advice was sought.

4.2.2. Segmentation

After identifying the KNMs, we segmented them in the following three ways to focus and prioritize our efforts:

• Sales region

  We grouped them by the regions in which they worked and the regions where they were most trusted by decision makers. (Note: KNMs may or may not be actual purchasers. They also may work in one sales region but influence purchasing decisions in multiple regions.)

• Potential sales impact

  High: The individual is trusted by a large number of decision makers with significant technology budgets.

  Medium: The individual is trusted by a smaller number of decision makers with significant technology budgets or by a larger number of decision makers with mid-sized budgets.

  Low: The individual is trusted by a smaller number of decision makers with smaller budgets.

• Ease of building a relationship

  High: There is a current relationship between a TechFirm employee and the KNM.

  Medium: A TechFirm employee has a relationship with an individual who is connected to the KNM.

  Low: The only relationship paths between a TechFirm employee and the KNM require two or more intermediaries.

4.2.3. Cross-Functional Team Assignments

To engage professionals within TechFirm more fully in this process, we then formed three cross-functional teams of three to four individuals representing sales, marketing, and technical expertise within TechFirm. On the basis of the segmentation conducted earlier, the teams grouped KNMs into the following three categories:

• High/Medium potential sales impact concentrated in one region

• High/Medium potential sales impact concentrated in more than one region

• Low potential sales impact

Each team was then assigned one of these groups and asked to research the following areas for each KNM in that group:

• Status of relationship with TechFirm

• Optimal path to engage with the KNM

• Level of advocacy or use of TechFirm's products

Each cross-functional team was given two weeks to complete the research and share its findings with the larger group.