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---
hypotheses:
  - name: "CLI_per_active_AM"
    description: "Teams might be over-or-under-utilizing their Account Managers"
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv"
      value_column: "CLI_per_active_AM"
      natural_name: "CLIs / Account Manager"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean.
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} of CLIs per Account Manager than the global mean ({ref_hypo_val}). This workload imbalance likely affects the team's ability to properly manage client engagements, impacting overall performance metrics.

  - name: "SLI_per_active_AM"
    description: "Teams are busy with SLIs and have not been able to cover the CLIs."
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv"
      value_column: "SLI_per_active_AM"
      natural_name: "SLIs / Account Manager"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean.
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} of SLIs per Account Manager than the global mean ({ref_hypo_val}). This suggests Account Managers are handling a different SLI workload, potentially diverting focus from CLI-related activities and affecting performance outcomes.
      
  - name: "sli_closed_won_pct"
    description: "Teams are busy with SLIs and have not been able to cover the CLIs."
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv"
      value_column: "sli_closed_won_pct"
      natural_name: "SLI Closed Won %"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean.
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} SLI Closed Won % than the global mean ({ref_hypo_val}). This suggests the team is experiencing different success rates with SLIs, which may be affecting resource allocation and attention to CLI-related activities.

  - name: "sli_added_and_closed"
    description: "Teams are busy with SLIs and have not been able to cover the CLIs."
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv" 
      value_column: "sli_added_and_closed"
      natural_name: "SLI Added & Closed"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean.
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} of SLIs added and closed than the global mean ({ref_hypo_val}). This suggests a different level of SLI in the region, potentially consuming Account Manager bandwidth that could otherwise be directed toward CLI.

  - name: "CI_w_KI_pct"
    description: "% of CI connected to key initiatives."
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv"
      value_column: "CI_w_KI_pct"
      natural_name: "% CIs with Key Initiatives"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean. 
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} of % CI connected with KI than the global mean ({ref_hypo_val}). This may cause high CLI lost rate as the KI was never spoken about in a client interaction.

  - name: "CI_per_CLI"
    description: "Specialists or Managers's effort is not aligned with the CLIs."
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv"
      value_column: "CI_per_CLI"
      natural_name: "CIs per CLI"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean.
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} of Client Interactions per CLI than the global mean ({ref_hypo_val}). This suggests potential misalignment between team effort and CLI priorities, affecting overall performance and conversion rates.

  - name: "CI_per_active_AM"
    description: "Teams with more client interactions than other teams. AMs have not been able to cover the book still."
    hypothesis_type: "single_dim"
    input_data:
      file: "hypothesis_input/CLI_CI_KI_hypothesis.csv"
      value_column: "CI_per_active_AM"
      natural_name: "CIs per Account Manager"
      region_column: "territory_l4_name"
    evaluation:
      method: "threshold_compare"
      direction: "opposite"
    insight_template: |
      Callout: {metric_name} in {region} is {metric_deviation}% {metric_dir} than Global mean.
      Root cause indicator: {region} has {hypo_delta} {hypo_dir} of Client Interactions per Account Manager than the global mean ({ref_hypo_val}). This suggests Account Managers have different interaction volumes, potentially impacting their ability to effectively manage and prioritize CLIs in their portfolio.