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href=\"https://www.snowflake.com/ja/analytics/business-intelligence/okr/\"\u003EOKR\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small"}},":itemsOrder":["text_894059747","text"]},"isBlogPage":false,"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","appliedCssClassNames":"snowflake-flexible-column-container-gray-10-bg"},"flexible_column_cont_663228916":{"id":"flexible-column-container-09bfa0b112","propertiesId":"hub-body","type":"2-column-60-40","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"medium","bottomPadding":"medium","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"propertiesCSSClasses":"page-section","backgroundImageOption":"none","flexible_column_content_container_1":{"additionalClasses":"longform-content","layout":"SIMPLE","id":"hub-body-content",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"callout__0":{"id":"text-0112fd838d","additionalClasses":"callout callout--general","text":"\u003Cp\u003E\u003Cb\u003EKPIの定義\u003C/b\u003E\u003C/p\u003E\r\n\u003Cp\u003EKPI（Key Performance Indicator：重要業績評価指標）とは、特定された事業目標に対する進捗状況を時系列で継続的に測定するために明確に定義された定量指標です。単なる全般的なデータ指標とは異なり、KPIは組織が重点的に評価、管理することを決定した特定の事業成果や目標数値に紐づいています。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"text__0":{"id":"text-cc1d072823","text":"\u003Cp\u003E既存のダッシュボードには、時間の経過とともに多様な数値指標が蓄積されていく傾向があります。四半期単位のプロジェクト推進のために新しい指標が追加され、役員からの突発的なレポート要求によって別の項目が加わり、かつて意思決定の判断材料として使われていた過去の指標が、事業方針の変更後も削除されずに残り続けます。最終的に、経営層向けのダッシュボード上に「重要（Key）」と称する指標が数十種類も乱立する事態に陥ります。\u003C/p\u003E\r\n\u003Cp\u003Eこの状態に達した時点で、該当指標群における\u003Ci\u003E「重要（Key）」\u003C/i\u003Eという本来の意義が失われてしまいます。\u003C/p\u003E\r\n\u003Cp\u003E米国国立標準技術研究所（NIST）関連の研究者が\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://pmc.ncbi.nlm.nih.gov/articles/PMC11010721/\"\u003E発表した調査\u003C/a\u003Eによると、KPIが組織の業績評価や意思決定において極めて重要な役割を担っているにもかかわらず、多くの企業や組織ではKPIの評価および改善が場当たり的なプロセスで運用されている実態が示されています。同研究では、個々のKPIが有効に機能しているかを検証する際、組織全体の事業目標やステークホルダーの意見を構造的に組み込んだ、より体系的な評価プロセスの導入が不可欠であると提言されています。\u003C/p\u003E\r\n\u003Cp\u003Eどの評価指標を最優先で注視すべきか、提示されたしきい値が何を意味するのか、そして数値の変動に対して、誰がどのようなアクションを取るべきかを組織全体で明確に定義している場合、実際に対応を要する重要なシグナルへ時間とリソースを効率的に集中させることができます。こうした明確な運用規律が存在しない場合、ダッシュボード上の指標群は現場の活用能力を超える速度で無計画に肥大化していきます。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_what-is-a-kpi":{"id":"title-v2-1523a8b816","additionalClasses":"anchor-title anchor-title--what-is-a-kpi","type":"heading2","lines":["KPIとは"],":type":"snowflake-site/components/title-v2"},"text_what-is-a-kpi_0":{"id":"text-0e882b482c","text":"\u003Cp\u003EKPI（Key Performance Indicator：重要業績評価指標）とは、設定された一定期間において、組織における重要な事業目標に対する進捗状況を測定するために使用される定量指標です。KPIの重要性は、単なる数値データの集計結果ではなく、そこに明確な意思決定上の役割が割り当てられている点にあります。すなわち、経営層やリーダーシップチームが、特定の戦略的判断や業務改善を実施する上で優先的に監視すべき最重要指標となるのです。\u003C/p\u003E\r\n\u003Cp\u003EすべてのKPIは指標に含まれますが、すべての指標がKPIとなるわけではないという原則を理解することが重要です。ウェブサイトのページビュー数、データベースのクエリ処理量、サポートチケットの起票件数、営業電話の架電数などは、いずれも事業活動の特定の側面を示すデータに過ぎません。これらも適切な文脈と事業目標が紐づくことでKPIとして機能する可能性があります。しかし、実務において有効に機能するKPIとして運用するためには、単なるデータのカウントを超えた、より高度で明確な指標定義と運用の枠組みが必要となります。チームは少なくとも、その計算式、単位、目標値または許容範囲、データオーナー、レビュー期間、および信頼できるデータソースを定めておく必要があります。これらの詳細を明確に定義しておくことで、何を測定しているのか、そして数値が変動した際に組織としてどう解釈すべきかが定まります。\u003C/p\u003E\r\n\u003Cp\u003EKPIの多くは定量的な数値ですが、定性的な指標を活用することも可能です。たとえば、従業員エンゲージメントや顧客感情などは定性的な評価から始まりますが、集計手順やスコアリング方法を一貫させることで、追跡可能な指標として運用できます。\u003C/p\u003E\r\n\u003Cp\u003E月間定額収益（MRR）を例に挙げてみます。「自社のMRRが1億5,000万円である」と報告するだけでは、現在の単なる事実状態を示しているに過ぎません。一方で、成長目標や年度末のMRRターゲットが設定され、進捗に責任を持つ経営幹部が割り当てられ、さらに成長率が一定のしきい値を下回った際に実行する具体的なアクションが合意されている場合、そのMRRはKPIとして機能していると言えます。単なる数値かKPIかの違いは、その数値の周囲にどのような運用体制やアクションの仕組みが存在しているかにあります。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ci\u003EMarriottが、標準化されたKPI、ガバナンスの効いたセマンティックモデル、信頼できるデータへの自然言語によるアクセスを基盤として、対話型分析エクスペリエンスを構築した方法をご覧ください。\u003C/i\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"yt_what-is-a-kpi_0":{"id":"embed-1d6f6ed61f","youtubeVideoId":"ZgM4_ZqkvJM","layout":"responsive","youtubeAspectRatio":"56.25","youtubeAutoPlay":false,"youtubeLoop":false,"youtubeMute":false,"youtubePlaysInline":false,"youtubeRel":false,"isLcpImage":false,"embeddableResourceType":"core/wcm/components/embed/v1/embed/embeddable/youtube","type":"EMBEDDABLE",":type":"snowflake-site/components/youtube"},"title_what-makes-a-kpi-key":{"id":"title-v2-2e41f6380f","additionalClasses":"anchor-title anchor-title--what-makes-a-kpi-key","type":"heading2","lines":["KPIに必要な6つの要素：「重要（Key）」と呼べる指標の条件"],":type":"snowflake-site/components/title-v2"},"text_what-makes-a-kpi-key_0":{"id":"text-4fcc97357d","text":"\u003Cp\u003Eある指標を重要として指定することは、組織の注力ポイントやリソースをどこに向けるかという戦略的な意思決定そのものです。仮に1つのダッシュボードに60個ものKPIが並んでいるとすれば、それはどの重要シグナルを優先して確認すべきかの判断をユーザーにそのまま丸投げしている状態と言えます。\u003C/p\u003E\r\n\u003Cp\u003E該当の指標が本当に「Key」と呼ぶにふさわしいかを判断するには、以下に示す6つの構成要素が明確に定義されているかをチェックするのが効果的です。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E目標（Objective）：\u003C/b\u003E組織として直接影響を与え、達成したい重要な事業成果は何か\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E測定指標（Measure）：\u003C/b\u003E目標に対する進捗を判断する上で、根拠となる最適なシグナルは何か\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E目標値（Target）：\u003C/b\u003Eどの数値、あるいはどの許容範囲を達成すれば十分なパフォーマンスとみなすか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E責任者（Owner）：\u003C/b\u003E数値シグナルを定期的に確認し、必要な対応や指示を出す責任者は誰か\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eレビュー頻度（Cadence）：\u003C/b\u003Eどのくらいのサイクル（日次、週次、月次など）で指標をレビューすべきか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E具体的なアクション（Action）：\u003C/b\u003E数値が想定範囲から外れた際、どのような意思決定や対策を実行に移すか\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003E最後のアクションに関する問いは、特に重要な意味を持ちます。たとえば、今期の顧客獲得単価が15%上昇したとします。それによって、マーケティングキャンペーンの予算調整、集客チャネルの配分見直し、価格設定の変更、あるいはその他の具体的な意思決定が実際に行われるかどうかが判断基準となります。数値が動いても誰も行動を変えないのであれば、その指標はKPIとして機能していません。\u003C/p\u003E\r\n\u003Cp\u003E目標値についても、自社の固有な状況や運用ニーズに合わせて設定する必要があります。業界レポートなどの外部ベンチマークは議論の出発点として活用できますが、企業規模、顧客属性、対象地域、ビジネスモデルなどの違いにより、汎用的な数値をそのまま適用すると判断を誤る恐れがあります。\u003C/p\u003E\r\n\u003Cp\u003Eレビューの頻度も同様に、実際の業務スピードに即して定めるべきです。たとえば、1時間単位で数値が変動し当日の迅速な介入を要するサプライチェーン指標と、四半期ベースで評価する従業員定着率の指標とでは、必要とされるデータの鮮度が大きく異なります。不必要に更新頻度だけを上げても、無駄なリソースを消費するだけで、意思決定の質の向上にはつながりません。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_types-of-kpis-leading-lagging-strategic-and-operational":{"id":"title-v2-ed42a503df","additionalClasses":"anchor-title anchor-title--types-of-kpis-leading-lagging-strategic-and-operational","type":"heading2","lines":["KPIの種類：先行指標・遅行指標・戦略指標・業務指標"],":type":"snowflake-site/components/title-v2"},"text_types-of-kpis-leading-lagging-strategic-and-operational_0":{"id":"text-577e97df9b","text":"\u003Cp\u003E単一のKPIだけで事業や組織の全体像を網羅できるケースはほとんど存在しません。ある数値が具体的に何を意味しており、どのような意思決定やアクションに繋がるのかを正しく評価するには、複数の視点から多角的に分析する必要があります。\u003C/p\u003E\r\n\u003Cp\u003E具体的には、全社レベルの事業成果を追跡するものか、または現場の業務プロセスを追跡するものか、すでに発生した結果を示しているのか、あるいは今後の成果に影響を与える要因を示しているのか、そしてインプットからアウトカムに至る一連のプロセスにおいてどこに位置しているのかといった軸で捉えることが重要です。\u003C/p\u003E\r\n\u003Ctable\u003E\r\n\u003Cthead\u003E\u003Ctr\u003E\u003Cth\u003E分類\u003C/th\u003E\r\n\u003Cth\u003E定義\u003C/th\u003E\r\n\u003Cth\u003E例\u003C/th\u003E\r\n\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003E戦略KPI\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003E全社レベルの経営目標に対する進捗状況\u003C/td\u003E\r\n\u003Ctd\u003E売上高成長率\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003E業務KPI\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003E個別のプロセスや業務アクティビティのパフォーマンス\u003C/td\u003E\r\n\u003Ctd\u003E注文リードタイム\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003E部門機能KPI\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003E特定の専門部門・機能内におけるパフォーマンス\u003C/td\u003E\r\n\u003Ctd\u003EMQLのパイプライン\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003E先行指標\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003E将来の結果に影響を与えることが期待されるインプットや行動\u003C/td\u003E\r\n\u003Ctd\u003E商談の新規創出数\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003E遅行指標\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003E業務活動の実行後に観測される確定的な事業成果\u003C/td\u003E\r\n\u003Ctd\u003E四半期売上高\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003Eインプット指標\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003Eプロセスに投入されるリソースやリソース容量\u003C/td\u003E\r\n\u003Ctd\u003E営業リソース\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003Eプロセス指標\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003E業務作業がどのように実行されているかのプロセス品質\u003C/td\u003E\r\n\u003Ctd\u003E営業サイクルの長さ\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003Eアウトプット指標\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003Eプロセスによって生成された直接的な成果物\u003C/td\u003E\r\n\u003Ctd\u003E提案書の提出件数\u003C/td\u003E\r\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cb\u003Eアウトカム指標\u003C/b\u003E\u003C/td\u003E\r\n\u003Ctd\u003Eそれらのアウトプットに伴って生じる最終的な事業結果\u003C/td\u003E\r\n\u003Ctd\u003E成約による獲得売上高\u003C/td\u003E\r\n\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\r\n\u003Cp\u003E意思決定の実務において、特に効果的なアプローチとなるのが先行指標と遅行指標の組み合わせです。\u003C/p\u003E\r\n\u003Cp\u003E先行指標はチームがこれから介入可能な領域、すなわちプロセスの上流に位置する阻害要因や推進要因に着目します。これに対し遅行指標は、実行された施策の最終結果を検証するための指標です。売上高、解約率、不具合発生率といった数値は、過去に発生した結果の記録をチームに提供します。\u003C/p\u003E\r\n\u003Cp\u003Eこれら両指標の相互関係は、1つの事業仮説として定義できます。たとえば、顧客の登録後1週間以内におけるプロダクトのアクティベーション率を向上させれば、90日後の顧客リテンション率が改善する、という仮説を立てたとします。この場合、初期アクティベーション率を先行指標、90日後のリテンション率を遅行指標として紐づけて管理します。組織は運用を重ねる中で、アクティベーション率の変動が実際にリテンション率の変動を再現性高く予測できているかを継続的に評価していく必要があります。顧客の購買行動やプロダクトの機能変更、あるいは競合など市場環境の変化によってこの相関関係が希薄化し、かつて有効であった先行指標の予測精度が大きく低下するケースが存在するためです。\u003C/p\u003E\r\n\u003Cp\u003Eまた、KPIの体系化においてはインプット→アウトプット→アウトカム（事業成果）という連鎖構造で整理する手法も非常に効果的です。投入された各種リソース（インプット）が業務プロセスを経て特定の成果物（アウトプット）を生み出し、その累積が最終的な事業成果（アウトカム）へと結実します。この一連の指標の連鎖を俯瞰して整理することにより、組織が最終的に目指すべき事業目標と、その前段階で観測できる現場レベルの運用シグナルを明確に区別して管理できるようになります。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"card_v2_types-of-kpis-leading-lagging-strategic-and-operational_0":{"id":"card-v2-a890410297","additionalClasses":"seo-customer","configurationStatus":{"configured":true,"message":""},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/customers/all-customers/case-study/nissin/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"活用事例を見る"},"title":{"id":"title","type":"heading4","lines":["日清食品"],":type":"snowflake-site/components/title-v2"},"image":{"id":"image","isLcpImage":false,"alt":"Nissin Logo","lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--ad003b42-ad6d-4424-a0b5-310e90b4f273/nissin%25403x.png?preferwebp=true&quality=85","height":"351","width":"624",":type":"snowflake-site/components/image"},"type":"content-card","layoutStyle":"horizontal","text":{"id":"text","text":"\u003Cp\u003E日清食品は、企業活動に関わるあらゆるデータを一元化する統合分析基盤をSnowflakeで構築しました。この基盤は、生産供給量の可視化やグローバル経営ダッシュボードの構築などにすでに活用されており、データドリブンな経営の実現を支えています。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"},":type":"snowflake-site/components/card-v2"},"title_how-to-choose-kpis-that-change-behavior":{"id":"title-v2-4ca5c14d98","additionalClasses":"anchor-title anchor-title--how-to-choose-kpis-that-change-behavior","type":"heading2","lines":["意思決定と行動変容を促すKPIの設定方法"],":type":"snowflake-site/components/title-v2"},"text_how-to-choose-kpis-that-change-behavior_0":{"id":"text-c409b85d07","text":"\u003Cp\u003E「すべての企業が管理すべき50のKPI」といった画一的なベストプラクティス集に頼るアプローチは、課題解決の手順として適切ではありません。実効性のあるKPI選定は、組織がどのような意思決定を行いたいのかを起点としてスタートさせる必要があります。意思決定の目的が明確化されて初めて、その事業成果を左右する主要な変数やドライバーを特定し、意思決定の判断材料となる有効なデータシグナルを選定し、それらの指標が現場における具体的なアクションを支援できるかを確認できます。KPI設計における本来の目的は、ダッシュボード上の項目数を増やすことではなく、現場や経営層の介入（具体的な意思決定やアクション）によって成果の差を生み出せる重点領域にリソースと注意を集中させるため、絞り込まれた適切な指標群（KPIセット）を確立することにあります。\u003C/p\u003E\r\n\u003Ch3\u003E意思決定から始める\u003C/h3\u003E\r\n\u003Cp\u003Eまず、組織が目指す戦略目標と、指標数値が想定範囲から逸脱した際にリーダーシップ層が実行すべきアクションを事前に定義します。こうすることで、手元のデータを無計画に集計するのではなく、組織の具体的な行動に直結した指標だけをKPIとして厳選できるようになります。次に、組織がコントロールしたい最終的な事業成果を明確にし、その成果が確定する前の段階で状況を察知できる先行指標へと段階的に遡って特定していきます。\u003C/p\u003E\r\n\u003Ch3\u003EKPIツリーによる構造化\u003C/h3\u003E\r\n\u003Cp\u003EKPIツリー（ドライバーツリー）は、達成したい事業成果と、それに影響を与える各種業務プロセス、現場行動、投入リソースとの関係を体系的に可視化するフレームワークです。これにより、確定的な遅行指標と、現場チームがまだ介入可能な先行指標とを明確に切り分けて整理できます。\u003C/p\u003E\r\n\u003Cp\u003Eたとえば、SaaSなどのソフトウェア企業が顧客リテンション率の向上を目指しているケースを考えます。KPIツリーを構築することで、リテンション率という結果をプロダクトのアクティベーションへ紐づけ、さらにそれをオンボーディングの完了率、初回価値提供までの時間、主要機能の活用頻度といった具体的な先行要素へと段階的に分解できます。この構造化アプローチにより、手元にあるプロダクト関連データを無計画にすべてダッシュボードへ並べる事態を避け、具体的な改善策や介入アクションへ直結する最重要指標のみにリソースを集中させることが可能になります。\u003C/p\u003E\r\n\u003Ch3\u003E候補となるKPIを検証する\u003C/h3\u003E\r\n\u003Cp\u003E候補となる指標が明確になったら、一貫した基準に照らしてそれぞれを評価します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E関連性：\u003C/b\u003E該当指標が、達成すべき事業目標と直接的かつ密接に結合しているか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E妥当性：\u003C/b\u003E組織が「計測している」と想定している事象を、その指標が歪みなく正しく測定できているか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eコントロール可能性：\u003C/b\u003E担当チームやオーナーが、自らの業務施策やアクションによってその数値を意図的に改善できるか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E適時性：\u003C/b\u003E問題の発生や予兆に対し、現場が適切な改善措置を講じられるタイミングで迅速にシグナルを取得できるか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eデータ可用性：\u003C/b\u003E信頼できるデータソースから、一貫した定義に基づき継続的かつ安定的に算出できるか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E感度：\u003C/b\u003E事業や現場の業務において意味のある変化が生じた際、それに伴って数値が適切に反応するか\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E操作への耐性：\u003C/b\u003E本質的な事業成果を伴わない形での数値調整や、指標の形骸化を容易に行えない構造になっているか\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003Eこの検証ステップを踏むことで、単に手元で計測可能なだけのデータを除外し、実務で意思決定や業務改善に真に寄与する有用なKPIのみへ候補を絞り込むことができます。\u003C/p\u003E\r\n\u003Ch3\u003Eガードレール指標の追加と目標値の設定\u003C/h3\u003E\r\n\u003Cp\u003E主要なKPIに対して、1つ以上のガードレール指標を組み合わせて運用することで、特定の評価軸における数値改善が、他の重要な業務領域やサービス品質に対して悪影響を及ぼしていないかを察知できるようになります。\u003C/p\u003E\r\n\u003Cp\u003Eたとえば、カスタマーサポート部門において「問い合わせ解決時間の短縮」を主要KPIとして設定する場合、それと並行して「顧客満足度」や「再問い合わせ発生率」をガードレール指標として追跡します。これにより、単に処理スピードや対応件数を向上させるだけでなく、許容できるサービス品質の範囲内（ガードレール内）で業務改善が達成されているかを総合的に評価することが可能になります。\u003C/p\u003E\r\n\u003Cp\u003E目標値を設定する際にも、自社のコンテキストの反映が欠かせません。過去の実績、利用可能なリソース容量、および事業戦略を考慮することで、単なる汎用的な業界ベンチマークだけに依存するよりも確固たる設定基盤を構築できます。理想的には、設定された目標値や許容範囲が具体的なアクションと直接連動している状態が望まれます。たとえば、「このしきい値を下回った場合は要因調査を実施する」「この想定範囲を逸脱した場合は投入リソースの再配分を行う」「この水準を上回った場合はプロジェクトやプログラムの拡大を検討する」といった運用モデルをあらかじめ定義しておくことが重要です。\u003C/p\u003E\r\n\u003Ch3\u003EKPIが生み出す行動を検証する\u003C/h3\u003E\r\n\u003Cp\u003Eあるデータ指標が組織内で注視されるようになると、現場の従業員やチームはその数値を意識した行動をとるようになります。さらに報酬や評価といったインセンティブが結びつくと、この傾向はより顕著になります。ある測定指標が目標値や評価基準として指定された瞬間、その指標は本来の計測基準としての有効性を失うという現象を指すグッドハートの法則は、このKPI運用上のリスクを的確に表しています。指標に対して組織的な圧力が加わると、本質的な事業成果を改善することなく、数値データのみを表面上良く見せる行動が誘発される恐れがあります。特に、単一の集計値に報酬や評価が強く依存している場合、営業ノルマ、生産性目標、カスタマーサポート評価などの指標においてこの形骸化リスクが顕著に現れます。\u003C/p\u003E\r\n\u003Cp\u003Eそのため、KPIを人事評価やインセンティブ体系へ正式に組み込む前に、一定期間のパイロット運用を実施することが推奨されます。パイロット運用期間中には、現場チームがその指標をどのように認識しているか、自らの業務でコントロール可能だと感じているか、そして数値が実際の判断に反映され始めた際にどのような意図せぬ行動やプロセス変化が生じるかを客観的に検証することが重要です。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_how-to-define-govern-and-retire-a-kpi":{"id":"title-v2-e588f47bef","additionalClasses":"anchor-title anchor-title--how-to-define-govern-and-retire-a-kpi","type":"heading2","lines":["KPIの定義・ガバナンス・ライフサイクル管理"],":type":"snowflake-site/components/title-v2"},"text_how-to-define-govern-and-retire-a-kpi_0":{"id":"text-ea4782426e","text":"\u003Cp\u003E選定されたKPIを実務で機能させるには、最初に作成された特定のダッシュボード内にとどまらず、組織全体や異なる分析環境においても一貫して解釈できる精密な指標定義が必要です。\u003C/p\u003E\r\n\u003Cp\u003E本番運用におけるKPIの定義スペックには、以下の項目を明記することが推奨されます。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003Eビジネス目標\u003C/li\u003E\r\n\u003Cli\u003Eビジネス名称（人が覚えやすいもの）\u003C/li\u003E\r\n\u003Cli\u003E計算式\u003C/li\u003E\r\n\u003Cli\u003E単位\u003C/li\u003E\r\n\u003Cli\u003E集計粒度\u003C/li\u003E\r\n\u003Cli\u003E抽出条件と集計軸\u003C/li\u003E\r\n\u003Cli\u003E単一の信頼できるデータソース\u003C/li\u003E\r\n\u003Cli\u003Eビジネスオーナー\u003C/li\u003E\r\n\u003Cli\u003E目標値または許容範囲\u003C/li\u003E\r\n\u003Cli\u003E更新頻度および想定レイテンシー\u003C/li\u003E\r\n\u003Cli\u003Eレビューの頻度\u003C/li\u003E\r\n\u003Cli\u003Eアクションのしきい値\u003C/li\u003E\r\n\u003Cli\u003Eガードレール指標\u003C/li\u003E\r\n\u003Cli\u003E適用開始日\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003Eこれらの詳細要素を明確に定義してドキュメント化することにより、ビジネス部門とデータチームの間で、指標の意味とその実装が結びつきます。たとえば\u003Ci\u003E顧客リテンション\u003C/i\u003Eを確認する際、分析者が「どの顧客連絡先が集計対象に含まれるのか」「集計期間がどのように算出されているのか」「財務部門とカスタマーサクセス部門のダッシュボードで共通の指標定義が使用されているのか」といった前提条件を推測しなければならないような運用状況は回避する必要があります。\u003C/p\u003E\r\n\u003Cp\u003E同時に、役割と責任の明確な分離も不可欠です。ビジネスオーナーは、該当KPIの意味付け、事業上の重要性、およびどの意思決定に紐づけるかを定義します。一方でデータオーナーは、その定義に基づいた集計ロジックの実装およびテストを実施し、基盤データの品質やパイプラインを維持管理した上で、後続の利用システムや\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/analytics/business-intelligence/tools/\"\u003EBIツール\u003C/a\u003Eへ指標データを安定供給する役割を担います。\u003C/p\u003E\r\n\u003Cp\u003E一度ガバナンスのもとで標準化された指標定義は、BIダッシュボード、アドホックなSQLクエリ、さらには\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/generative-ai/\" target=\"_self\"\u003E生成AI\u003C/a\u003Eや\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/fundamentals/large-language-model/\" target=\"_self\"\u003ELLM\u003C/a\u003Eアプリケーションに至るまで、すべての消費エンドポイントにおいて共通のセマンティックロジックとして参照されるべきです。各BIツールや分析環境ごとに計算ロジックを個別定義してしまうと、指標の表記揺れや乖離を引き起こす要因となります。データ抽出フィルター、テーブル結合条件、集計粒度、日付計算ロジックなどのわずかな差異が蓄積することで、一見同じ名称でありながら算出結果が食い違う複数のKPI数値が組織内に乱立することになります。\u003C/p\u003E\r\n\u003Cp\u003Eデータ検証テストは、単に集計計算の正しさを検証するだけにとどめるべきではありません。データの欠損やパイプライン処理の遅延、ソースシステムの仕様変更、テーブル結合時の挙動変化、集計粒度の変容などは、いずれも出力される指標数値を変動させる要因となります。そのため、認定済みの正確な基準データとの突き合わせ照合を行うとともに、集計ロジックや計算式の変更を行う際は本番環境へ反映する前の事前検証を徹底する必要があります。\u003C/p\u003E\r\n\u003Cp\u003Eまた、指標の認定後も\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/data-governance/\"\u003Eデータガバナンス\u003C/a\u003Eを継続的に運用していくことが重要です。KPIのライフサイクルは、たとえば提案→検証→認定→監視→改訂→廃止という流れで管理できます。指標の定義を変更する際に適用開始日を記録しておけば、定義の変更をまたいで過去データと比較する場合でも、数値の意味を正しく解釈できます。\u003C/p\u003E\r\n\u003Cp\u003Eさらに、不要となった指標の廃止プロセスもガバナンスにおける重要な運用の要素です。上位の事業戦略目標が変更された場合、ビジネスオーナーが該当数値に基づくアクションを起こさなくなった場合、基盤データの信頼性が著しく低下した場合、あるいは数値の不適切な操作が常態化した場合は、そのKPIが寿命を迎えたと判断すべき明確なシグナルとなります。なお、先行指標に関してはもう1つ固有の検証視点が必要です。先行指標と遅行指標との間に存在していた仮説や相関関係が希薄化している場合、その先行指標の数値を最適化し続けても、組織の意思決定を誤った方向へ導いてしまうリスクが存在します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_how-to-define-govern-and-retire-a-kpi_0":{"id":"text-ad75c14ca4","additionalClasses":"callout callout--tip","text":"\u003Cp\u003E\u003Cstrong\u003Eクイックヒント\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E集計計算式の定義と併せて、例外条件や例外データなどのエッジケースも確実にドキュメント化しておくことが重要です。一見同じKPIでありながら異なる実装環境で数値の不一致が発生する場合、その原因の多くはデータ除外条件、遅延データの扱い、集計期間の境目、あるいは顧客ステータス遷移の解釈の違いに起因しています。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"title_kpi-examples-by-business-function":{"id":"title-v2-5479b74d11","additionalClasses":"anchor-title anchor-title--kpi-examples-by-business-function","type":"heading2","lines":["部門別のKPIの例"],":type":"snowflake-site/components/title-v2"},"text_kpi-examples-by-business-function_0":{"id":"text-167bbc147a","text":"\u003Cp\u003E最も有用なKPIは、各部門や機能が担う意思決定の性質によって大きく変化します。単独の指標をピックアップするのではなく、最終結果を示す遅行指標と、早期の対応や介入を可能にする先行指標をセットで組み合わせて定義することが不可欠です。以下に、代表的な業務機能別の具体例を挙げます。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E財務：\u003C/b\u003Eキャッシュコンバージョンサイクル（CCC）や予算実績差異といった確定的指標に、将来のキャッシュ予測や予測需要シグナルを組み合わせます。これにより、運転資本の最適化や経営リソースの配分に関する意思決定を迅速かつ的確に行えるようになります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eセールス：\u003C/b\u003E受注率や売上目標達成率は過去の事業成果を示します。これに対し、パイプラインカバレッジ、認定商談の新規創出数、ならびに商談サイクルの進捗は、将来の成果を左右する先行指標となります。営業リーダーはこれらの指標を組み合わせることで、メンバーへのコーチング、人員キャパシティ計画、チャネル投資の判断に活用できます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eマーケティング：\u003C/b\u003Eマーケティング起点の創出売上高や生成パイプライン額は、マーケティング活動の最終的な事業成果を示します。一方で、適格需要の創出数や各フェーズのコンバージョンシグナルは、最終成果に向けた進捗プロセスや成果に至る要因を定量的に分析するのに役立ちます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E業務・サプライチェーン：\u003C/b\u003E納期遵守率や不具合発生率といった結果指標を、設備や人員の稼働キャパシティ、サプライヤーリードタイム、直行率などの先行要素と組み合わせて管理します。運用プロセスにおける早期の兆候を把握することで、最終的なパフォーマンスが確定する前に、適切な人員配置、設備メンテナンス、プロセス改善のアクションを講じることが可能になります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E人事（HR）：\u003C/b\u003E優秀な人材の離職率は遅行指標です。これに対し、従業員エンゲージメント、マネージャーのマネジメント有効性、オファー承諾率などの指標は、組織や労働環境のコンディションを把握するための複合的な視点を提供します。なお、人事評価や報酬がこれらの指標に直接連動するケースでは、指標の不正操作や不公平な評価結果を防ぐため、ガードレール指標の設定および定性的な評価レビューの併用が特に重要となります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eカスタマーチーム（カスタマーサクセス・サポート）：\u003C/b\u003Eリテンション率や解約率といった事業結果は、プロダクトの利用定着度、継続的な未解決課題の発生状況、および問い合わせ解決シグナルと併せて多角的に評価することが可能です。これにより、解約リスクの早期検知や、CSチームによる事前のアプローチが効果を発揮する顧客を的確に特定できるようになります。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_okrs-north-star-metrics-and-balanced-scorecards":{"id":"title-v2-10682e7711","additionalClasses":"anchor-title anchor-title--okrs-north-star-metrics-and-balanced-scorecards","type":"heading2","lines":["KPIとKGI・OKRなど関連フレームワークの違い"],":type":"snowflake-site/components/title-v2"},"text_okrs-north-star-metrics-and-balanced-scorecards_0":{"id":"text-0ebcfac5ac","text":"\u003Cp\u003EKPIは多くの場合、組織のパフォーマンス管理や目標設定を行う広範なフレームワークと組み合わせて活用されますが、それぞれのフレームワークは目的に応じて異なる役割を果たします。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003EKGI（Key Goal Indicator：重要目標達成指標）\u003C/b\u003Eは、売上高や利益など、組織が最終的に達成すべきゴールを示す指標です。KPIは、KGIの達成に向けてプロセスが順調に進んでいるかを測る中間指標と位置付けられます。一般的には、KGIを起点に、その達成に欠かせない重要成功要因（KSF：Key Success Factor）を特定し、それを数値化したものをKPIとして設定します。本ガイドの分類で言えば、KGIは最上位の遅行指標、KPIはそこに至るまでの先行指標やプロセス指標にあたります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E目標と主要な成果（\u003C/b\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/analytics/business-intelligence/okr/\"\u003E\u003Cb\u003EOKR\u003C/b\u003E\u003C/a\u003E\u003Cb\u003E）\u003C/b\u003Eは、一定の期間（四半期や年間など）内に達成すべき定性的な目標（Objective）と、その達成度を測定する定量的な成果指標（Key Results）を設定し、組織の変革や集中的な成長を推進するためのフレームワークです。定性的な目標が組織の進むべき方向性を示すのに対し、主要な成果はその定めた変化が確実に達成されたことを示す定量的な根拠となります。通常運用されているKPIであっても、チームが特定のOKR実施期間中にその数値をベースラインからターゲット数値まで改善することを明確にコミットした場合、主要な成果として定義できます。一方で、多くの業務KPIは、業務プロセスの正常性や健全性を常時モニタリングするために用いられるため、特定の期限を設けず継続的に監視され続けます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eノーススターメトリック（North Star Metric：NSM）\u003C/b\u003Eは、プロダクト組織全体が創出する顧客価値を可視化し、組織全員で共有する単一の最重要指標です。ただし、ノーススターメトリック単体のみでプロダクト運用を行うことは推奨されません。その数値を支える各種インプット指標やガードレール指標で構成された小規模なKPIツリーを構築することで、何がノーススターの変動に寄与しているのかを正確に把握できるようになります。また、特定機能のみの局所最適化によって、プロダクトの全体品質、ユーザーからの信頼、あるいは事業の収益性が阻害されるリスクを防止できます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/en/analytics/business-intelligence/strategy/balanced-scorecard/\"\u003E\u003Cb\u003Eバランススコアカード\u003C/b\u003E\u003C/a\u003Eは、財務、顧客、社内プロセス、学習と成長という4つの主要な視点から事業戦略と各種パフォーマンス指標を構造的に整理する伝統的なマネジメントフレームワークです。バランススコアカードでは複数の側面に分散して注意を向けることで、単一の成果指標のみを運用する場合と比べ、組織全体のパフォーマンスに対するより俯瞰的で包括的な視点を経営層やリーダーシップ層へ提供します。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003Eどのフレームワークを採用する場合であっても、共通して重要なのは明確な事業戦略を軸として各種指標を構造化するという点です。そして、その基盤を支える実務的な測定規律（指標の厳密な定義、目標値の設定、オーナーシップの明確化、具体的なアクションとの連動）を提供するのが、適切なKPI設計の役割となります。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_okrs-north-star-metrics-and-balanced-scorecards_0":{"id":"text-18a3ee8803","additionalClasses":"callout callout--warning","text":"\u003Cp\u003E\u003Cstrong\u003Eよくある落とし穴\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E代表的な1つの最上位KPIのみをもって、事業全体のパフォーマンスを把握できたと誤認してしまうケースが散見されます。包括的な最上位指標に対して、それを補完する各種先行指標やガードレール指標をセットで組み合わせて運用することにより、特定の領域での数値改善が、他の重要な業務領域における悪化や歪みを覆い隠していないかを的確に察知できるようになります。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"title_how-snowflake-supports-governed-kpis":{"id":"title-v2-ac30a2dddc","additionalClasses":"anchor-title anchor-title--how-snowflake-supports-governed-kpis","type":"heading2","lines":["ガバナンスされたKPIの運用を支えるSnowflake"],":type":"snowflake-site/components/title-v2"},"text_how-snowflake-supports-governed-kpis_0":{"id":"text-2a4aab5888","text":"\u003Cp\u003E複数の分析ツールやBIインターフェースにまたがってKPIを運用する組織において数値の一貫性を維持できるかどうかは、集計ロジックがどのレイヤーに定義されているかに大きく依存します。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" href=\"https://docs.snowflake.com/ja/user-guide/views-semantic/overview\" target=\"_blank\"\u003ESnowflakeセマンティックビュー\u003C/a\u003Eは、指標、ファクト、分析軸、およびそれらの関連性を、データ基盤に近いスキーマレベルのオブジェクトとして一元定義する機能です。セマンティックビュー上で定義されたビジネス指標は、SQLクエリ、各種BIツール、\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/fundamentals/ai-applications/\" target=\"_self\"\u003EAIアプリケーション\u003C/a\u003Eの各インターフェースから共通して再利用できるため、計算ロジックの重複定義や、異なるツール間における数値の乖離を防ぐことが可能です。\u003C/p\u003E\r\n\u003Cp\u003Eまた、このようにガバナンスされたビジネスロジックは、\u003Ca href=\"https://www.snowflake.com/ja/fundamentals/natural-language-processing/\" target=\"_self\"\u003E自然言語処理\u003C/a\u003Eによるデータ分析やデータ探索においても重要な前提コンテキストとして機能します。たとえばCortex Agentsは、構造化データに対するユーザーからの問いかけに回答する際、セマンティックビュー内に保持された各種定義やリレーションシップを参照します。これにより、利用者が自然言語でガバナンス対象の指標について質問した場合でも、ダッシュボードや標準レポートと同一のビジネスロジックに基づいて正確な回答を生成できます。\u003C/p\u003E\r\n\u003Cp\u003Eその他の各種インターフェースを活用することで、ガバナンスされた指標の利用範囲はさらに拡大します。SnowflakeのAI開発者向けIDEであるCoCo Desktopを利用すれば、自然言語を用いてSnowflake上のデータをクエリし、そのUI上で直接集計結果を確認できます。また、\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/product/snowflake-cowork/\" target=\"_self\"\u003ESnowflake CoWork\u003C/a\u003Eは、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/artificial-intelligence/agents/autonomous-agents/\"\u003E自律型エージェント\u003C/a\u003Eやツール連携を介して、ガバナンス管理された各種指標を組織全体へ展開することを可能にします。いずれの先進的なテクノロジーを採用する場合であっても、ITシステムや\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/\" target=\"_self\"\u003EAI\u003C/a\u003Eはあくまで一元化された指標定義を正確に保持する基盤に過ぎません。どの指標を重点追跡すべきか、設定された目標値が事業上何を意味するのか、そして数値の変動に対してどのような意思決定、アクションを講じるべきかという本来の判断責任は、常にビジネスリーダー側に存在します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_from-kpi-measurement-to-action":{"id":"title-v2-7c49c90abb","additionalClasses":"anchor-title anchor-title--from-kpi-measurement-to-action","type":"heading2","lines":["KPI測定から現場のアクションへの転換"],":type":"snowflake-site/components/title-v2"},"text_from-kpi-measurement-to-action_0":{"id":"text-078c208205","text":"\u003Cp\u003E優れたパフォーマンスを発揮するKPIシステムは、管理対象とする指標を厳密に絞り込んでいます。このような運用モデルでは、事業戦略上の最重要目標に直結した少数の指標に対してのみ組織的なリソースと注意を継続的に集中させます。さらに、それらの指標定義を厳密に規定した上で、データのシグナルが変動した際に現場やマネジメント層がどのようなアクションを講じるべきかを明確にしています。\u003C/p\u003E\r\n\u003Cp\u003Eデータ測定の仕組みを継続的に実用的な状態で維持するには、構築段階で適用した規律を運用フェーズでも維持し続ける必要があります。すなわち、先行指標と事業成果との相関関係を定期的に検証すること、多様な分析インターフェースやツール間でセマンティック定義の一貫性を保持すること、そして事業価値を生み出さなくなった不要な指標を廃止していくことです。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_from-kpi-measurement-to-action_0":{"id":"text-dc861a8ca3","additionalClasses":"callout callout--general","text":"\u003Cp\u003E\u003Cstrong\u003E重要なポイント\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E効果的なKPIシステムは、組織の事業戦略と現場の継続的な意思決定とを密接に結びつけます。これを実現するには、明確なオーナーシップ、信頼できる基盤データ、適切なレビュー周期、そして事業パフォーマンスが意図した方向へ実際に推移しているかを見極めるための十分なコンテキストが不可欠となります。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"}},":itemsOrder":["callout__0","text__0","title_what-is-a-kpi","text_what-is-a-kpi_0","yt_what-is-a-kpi_0","title_what-makes-a-kpi-key","text_what-makes-a-kpi-key_0","title_types-of-kpis-leading-lagging-strategic-and-operational","text_types-of-kpis-leading-lagging-strategic-and-operational_0","card_v2_types-of-kpis-leading-lagging-strategic-and-operational_0","title_how-to-choose-kpis-that-change-behavior","text_how-to-choose-kpis-that-change-behavior_0","title_how-to-define-govern-and-retire-a-kpi","text_how-to-define-govern-and-retire-a-kpi_0","callout_how-to-define-govern-and-retire-a-kpi_0","title_kpi-examples-by-business-function","text_kpi-examples-by-business-function_0","title_okrs-north-star-metrics-and-balanced-scorecards","text_okrs-north-star-metrics-and-balanced-scorecards_0","callout_okrs-north-star-metrics-and-balanced-scorecards_0","title_how-snowflake-supports-governed-kpis","text_how-snowflake-supports-governed-kpis_0","title_from-kpi-measurement-to-action","text_from-kpi-measurement-to-action_0","callout_from-kpi-measurement-to-action_0"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium"},"flexible_column_content_container_2":{"additionalClasses":"hub-sidebar","layout":"SIMPLE","id":"hub-body-aside",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"container":{"additionalClasses":"sticky-sidebar","gridClassNames":"aem-Grid 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