A modified force field problem-solving model, combined with qualitative and quantitative research, is used to analyze a political challenge and develop a campaign strategy.
A seven-term incumbent Mayor of a capitol city lost his last primary election. It was his first ever election loss after winning elections by a landslide for 35 years. His campaign manager wanted the mayor to run in the general election as a write-in candidate. The campaign manager knew that the Mayor wouldn't consider running unless there was a high probability of winning. The challenge was to determine with a high rate of certainty if the Mayor could win a general election as a write in candidate and, if a general election campaign was launched, to create a winning campaign strategy.
Robert Nelson was engaged to apply a modified force field problem-solving model as the analytical methodology to determine the likelihood of winning and to develop a winning general election strategy.
A comprehensive analysis of the primary was conducted. The application of a force field problem-solving model surfaced 51 environmental forces (driving forces) pushing toward a victory for the incumbent in the general election and 59 forces creating barriers to a victory (restraining forces). Twenty-seven driving forces and 19 restraining forces related to the opponents campaign were identified. Nelson facilitated a series of sessions to develop assumptions about the general election campaign, including voter block behavior assumptions. Post-primary polling data was analyzed and a psycho-demographic profile created for each precinct. Finally, general election vote scenarios were generated.
Six strategic issues were formulated that, if addressed in a general election write-in bid, would result in victory. Tactics and action steps to achieve the strategic goals were also developed, along with a new campaign staffing structure.
In the end, the candidate chose not to run, notwithstanding the high probability of winning.