Many businesses still lose hours each day to manual, repetitive work—invoice entry, reporting, onboarding, customer inquiries. Modern automation technologies like RPA and AI can take over these tasks, boosting productivity, accuracy, and employee satisfaction. In Indonesia, 83% of businesses expect digitalization to reshape operations by 2030. At PT Sazanka Henig Solusi, we help organizations unlock automation using proven tools like UiPath and Microsoft Power Automate. Let us help you transform the repetitive into the remarkable.

Indonesia’s luxury fashion market is growing fast—but so are the challenges. Retailers are under pressure to manage high-value inventory with precision, forecast demand accurately, and break down silos between sales, finance, and buying teams. Relying on spreadsheets and disconnected planning systems is no longer sustainable in today’s fast-moving, trend-sensitive environment. This article explores how intelligent merchandise financial planning can help luxury retailers in Indonesia overcome inventory risks, close forecasting gaps, and unify their operations. Discover how platforms like Board empower data-driven decisions, optimize stock levels, and align strategy with execution.

The telecommunications industry in Indonesia, a vital backbone of the nation’s digital economy, is currently undergoing a major transformation. It is a giant industry with an estimated market size of USD 18.12 billion in 2025, projected to reach USD 23.97 billion by 2030, growing at a CAGR of 5.76% during the forecast period (2025–2030). This growth has been mainly caused by a possible increase in users. However, it may also be fueled by more revenue per user as the nation's earnings rise. As the sector becomes more competitive and customer expectations evolve rapidly, traditional planning and forecasting methods have proven to be inadequate. In 2025 and beyond, telecommunications companies must move beyond manual, outdated planning approaches and utilize Machine Learning and AI-driven solutions to remain relevant.
