روشی نظاممند برای اولویتبندی ذینفعان در کمیتهی راهبری حکمرانی داده بر اساس اکوسیستم دادهی سازمان
محورهای موضوعی : فناوری اطلاعات و دانش
فهیمه سلیمی کوچی
1
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ابوالقاسم سرآبادانی
2
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1 - گروه مدیریت فناوری اطلاعات، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس
2 - گروه مدیریت فناوری اطلاعات، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران
کلید واژه: حکمرانی داده, کمیتهی راهبری حکمرانی داده, اکوسیستم داده, اولویتبندی ذینفعان, DESPA,
چکیده مقاله :
در اقتصاد دادهمحور امروز، حکمرانی داده صرفاً یک الزام فنی و کنترلی نیست، بلکه قابلیتی راهبردی برای ارتقای کارایی، تضمین انطباق و خلق ارزش از داراییهای دادهای به شمار میرود. در این میان، شناسایی ذینفعان کلیدی و تعیین نحوه مشارکت آنان در کمیته راهبری، یکی از مسائل مهم و در عین حال کمتر تبیینشده در حوزهی حکمرانی داده است. این پژوهش با هدف پاسخگویی به این مسئله، الگوریتمی نظاممند و دادهمحور با عنوان «DESPA» برای شناسایی و اولویتبندی ذینفعان اکوسیستم داده ارائه میکند. الگوریتم پیشنهادی با درنظرگرفتن اهمیت مجموعهداده برای کسبوکار، فراوانی تبادل و جهت جریان داده، اهمیت نسبی ذینفعان را محاسبه و آنان را از نظر نوع مشارکت در کمیته راهبری طبقهبندی میکند. نوآوری پژوهش در فراهمکردن مبنایی کمّی، شفاف و تکرارپذیر برای تبدیل روابط واقعی تبادل داده به پیشنهاد مشخصی درباره ترکیب کمیته و نقش هر ذینفع است. قابلیت کاربرد روش با اجرای آن در سناریوی واقعنمای یک هلدینگ فرضی پتروشیمی بررسی شد. نتایج نشان داد که DESPA میتواند میان تعداد روابط دادهای و اهمیت واقعی ذینفعان تمایز قائل شود و آنان را در سه سطح هستهای، مشورتی و عادی طبقهبندی کند. بر این اساس، روش پیشنهادی ضمن کاهش اتکا به قضاوتهای سلیقهای، امکان تعیین نوع عضویت ذینفعان در کمیته راهبری حکمرانی داده را فراهم میسازد و میتواند بهعنوان ابزاری تصمیمیار در سازمانهای بزرگ و چندذینفعی به کار گرفته شود.
In today’s data-driven economy, data governance is not merely a technical and control requirement but a strategic capability for enhancing efficiency, ensuring compliance, and creating value from data assets. In this context, identifying key stakeholders and determining how they should participate in the data governance steering committee remain important yet insufficiently addressed issues. To address this gap, this study proposes the Data Ecosystem Stakeholder Prioritization Algorithm (DESPA), a systematic, data-driven method for identifying and prioritizing stakeholders within an organization’s data ecosystem. By considering the business importance of datasets, the frequency of data exchanges, and the direction of data flows, DESPA calculates stakeholders’ relative importance and classifies them according to their appropriate mode of participation in the steering committee. The study’s main contribution is to provide a quantitative, transparent, and reproducible basis for translating data-exchange relationships into specific recommendations regarding committee composition and stakeholder roles. The applicability of the method was examined through a realistic scenario involving a hypothetical petrochemical holding company. The results demonstrate that DESPA can distinguish between the number of data relationships and stakeholders’ substantive importance, classifying them into three categories: core, advisory, and regular stakeholders. Accordingly, the proposed method reduces reliance on subjective judgments, supports the determination of appropriate membership arrangements in data governance steering committees, and can serve as a decision-support tool for large, multi-stakeholder organizations.
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