SME investment best strategies. Outliers for assessing how to optimize performance

TL;DR

This study uses extreme value statistics to identify investment strategies that predict SME performance during financial crises, highlighting the importance of growth in tangible assets for positive outcomes.

Contribution

It introduces a novel application of extreme value analysis to assess SME investment timing and levels for performance forecasting during crises.

Findings

Outliers with positive performance had low but growing TTA.

SMEs with stagnant TTA before crises tended to perform poorly.

Extreme value distributions reveal key investment patterns for success.

Abstract

Any research on strategies for reaching business excellence aims at revealing the appropriate course of actions any executive should consider. Thus, discussions take place on how effective a performance measurement system can be estimated, or/and validated. Can one find an adequate measure (i) on the performance result due to whatever level of investment, and (ii) on the timing of such investments? We argue that extreme value statistics provide the answer. We demonstrate that the level and timing of investments allow to be forecasting small and medium size enterprises (SME) performance, - at financial crisis times. The "investment level" is taken as the yearly total tangible asset (TTA). The financial/economic performance indicators defining growth are the sales or total assets variations; profitability is defined from returns on investments or returns on sales. Companies on the Italian Stock Exchange STAR Market serve as example. It is found from the distributions extreme values that outlier companies (with positive performance) are those with the lowest but growing TTA. In contrast, the SME with low TTA, but which did not increase its TTA, before the crisis, became a negative outlier. The outcome of these statistical findings should suggest strategies to SME board members.