英文标题：
《Business Dynamics in KPI Space. Some thoughts on how business analytics
can benefit from using principles of classical physics》
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作者：
Alex Ushveridze
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最新提交年份：
2017
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英文摘要：
The biggest problem with the methods of machine learning used today in business analytics is that they do not generalize well and often fail when applied to new data. One of the possible approaches to this problem is to enrich these methods (which are almost exclusively based on statistical algorithms) with some intrinsically deterministic add-ons borrowed from theoretical physics. The idea proposed in this note is to divide the set of Key Performance Indicators (KPIs) characterizing an individual business into the following two distinct groups: 1) highly volatile KPIs mostly determined by external factors and thus poorly controllable by a business, and 2) relatively stable KPIs identified and controlled by a business itself. It looks like, whereas the dynamics of the first group can, as before, be studied using statistical methods, for studying and optimizing the dynamics of the second group it is better to use deterministic principles similar to the Principle of Least Action of classical mechanics. Such approach opens a whole bunch of new interesting opportunities in business analytics, with numerous practical applications including diverse aspects of operational and strategic planning, change management, ROI optimization, etc. Uncovering and utilizing dynamical laws of the controllable KPIs would also allow one to use dynamical invariants of business as the most natural sets of risk and performance indicators, and facilitate business growth by using effects of parametric resonance with natural business cycles.
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中文摘要：
目前在商业分析中使用的机器学习方法的最大问题是，它们不能很好地概括，并且在应用于新数据时常常失败。解决这个问题的一个可能的方法是利用从理论物理中借用的一些内在确定性附加组件来丰富这些方法（几乎完全基于统计算法）。本说明中提出的想法是将表征单个企业的一组关键绩效指标（KPI）分为以下两个不同的组：1）主要由外部因素决定的高度不稳定的KPI，因此企业难以控制；2）由企业自身确定和控制的相对稳定的KPI。看起来，第一组的动力学可以像以前一样，使用统计方法来研究，而为了研究和优化第二组的动力学，最好使用类似于经典力学最小作用原理的确定性原理。这种方法在商业分析领域开辟了一系列有趣的新机会，有许多实际应用，包括运营和战略规划、变更管理、ROI优化、，等。发现和利用可控KPI的动态规律，还可以将业务的动态不变量用作最自然的风险和绩效指标集，并通过利用自然商业周期的参数共振效应促进业务增长。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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