哈喽，大家好，火哥这篇文章，主要来分析经营分析总被骂"瞎忙活"？4步打通业财，2025年企业必看 很多公司的经营分析报告，说来说去就三句话：收入低了搞高，成本高了搞低，再甩一堆同比环比数 据。 业务部门看了直撇嘴，觉得这分析纯属"正确的废话"，半点用没有。 其实问题根本不在数据本身，而在于没打通业务和财务的关节——财务不懂业务痛点，业务不懂财务逻 辑，分析自然成了空架子。 还有些是维持运营的基础服务，比如客服；另外像物流、售后这种，订单越多花钱越多，得靠规模摊薄 成本。 不少公司做分析，总爱把收入归销售、成本归供应，搞得各部门像脱节的齿轮。 销售只顾冲业绩，拿订单时不管产品能不能做、利润够不够；供应只顾压成本，不管市场需求变没变， 最后问题全堆到一起。 有些投入能直接拉收入，比如新增的高ROI销售渠道；有些得和其他动作配合才起效，比如促销、广告 加研发的联动； 2025年都到了，搞经营分析早不是简单列数字，关键是让每笔账都能对应到具体业务，每个动作都能算 出真实回报。 实际上，销售乱承诺客户、推广烧钱没流量，这些都会让供应链计划彻底失效。 今天就把这套能落地的方法说透，分4步走，小公司也能直接用。 2025年 ...

Core Insights - The article emphasizes the importance of integrating financial, business, and organizational data to enhance operational analysis in banks, transforming it from passive reporting to proactive insights [1][4][32] Financial Performance - The bank's operating income reached 1.753 billion, reflecting a year-on-year growth of 16.79%, indicating stable profitability quality [4] - The total liabilities amount to 30.22 billion, showcasing the bank's liability stability [7] Asset and Liability Analysis - The analysis dashboard provides insights into loan structures, including corporate and personal loans, with an average corporate loan balance of 21.956 million [7][10] - The bank's deposit scale is 30.22 billion, with a focus on the stability of liabilities and market financing dependencies [7] Customer Insights - The analysis identifies high-contribution customers and optimizes resource allocation, enhancing the bank's overall operational efficiency [13] - The economic value added (EVA) of customers is assessed, revealing potential for profit contribution and areas for optimization [11] Risk Management - The article discusses the importance of tracking overdue loans and identifying periods of increased risk, which aids in dynamic risk provisioning [16][17] - Customer demographic analysis helps in recognizing core value segments and potential high-risk groups, facilitating targeted risk management strategies [21] Operational Efficiency - The bank's internal operations are analyzed to optimize branch resource allocation and improve service quality [22][27] - Time-based analysis reveals seasonal trends and peak business hours, allowing for better staffing and resource management [28] Strategic Decision-Making - The integration of customer structure and operational data enables precise service delivery and marketing strategies tailored to different demographic groups [31] - A data-driven operational analysis system is essential for strategic decision-making and refined management practices in the banking sector [32]