Identifying relevant metrics as performance indicators in a B2B SaaS company: Case Smartly.io
| dc.contributor | Aalto-yliopisto | fi |
| dc.contributor | Aalto University | en |
| dc.contributor.advisor | Pöyry, Essi | |
| dc.contributor.author | Auvinen, Riku | |
| dc.contributor.school | Perustieteiden korkeakoulu | fi |
| dc.contributor.supervisor | Maula, Markku | |
| dc.date.accessioned | 2017-04-13T10:26:25Z | |
| dc.date.available | 2017-04-13T10:26:25Z | |
| dc.date.issued | 2017-04-05 | |
| dc.description.abstract | Software-as-a-Service (SaaS) companies often operate in new, fast moving markets and industries making the measurement of operational performance more complicated as in e.g. traditional manufacturing business. When the companies are in the “hyper-growth” stage, generating massive losses due to investments in R&D and market penetration is not uncommon. Managers of such companies are often tied in day-to-day work in e.g. sales and recruiting, having limited time for business analysis and making sense of financial and non-financial data. The combination creates an evident need for clear performance indicators that show the health of the underlying business with a glance. To address this issue, a clear set of key performance indicators (KPI) is identified with the goal that the indicators would drive long-term shareholder value creation, motivated by the efficient markets theorem which states that investors value healthy companies with strong future cash flow potential. The KPI’s will be based on a theoretical framework derived from valuation theory, prior research regarding valuation of fast growing technology companies and metrics that investors follow in such companies. The theoretical framework is tested by gathering empirical evidence on whether the valuation factors can be observed in valuation levels of publicly listed SaaS companies by performing regression analysis with valuation level as the dependent variable and financial statement information as independent variables. The results show that valuation levels are strongly correlated with revenue growth and potential future profitability. | en |
| dc.ethesisid | Aalto 8606 | |
| dc.format.extent | 60 | |
| dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/25159 | |
| dc.identifier.urn | URN:NBN:fi:aalto-201704133592 | |
| dc.language.iso | en | en |
| dc.location | P1 | |
| dc.programme | Master’s Programme in Industrial Engineering and Management | fi |
| dc.programme.major | Strateginen johtaminen | fi |
| dc.programme.mcode | Strateginen johtaminen | fi |
| dc.subject.keyword | SaaS | en |
| dc.subject.keyword | software-as-a-service | en |
| dc.subject.keyword | valuation | en |
| dc.subject.keyword | metrics | en |
| dc.subject.keyword | kpi | en |
| dc.title | Identifying relevant metrics as performance indicators in a B2B SaaS company: Case Smartly.io | en |
| dc.type | G2 Pro gradu, diplomityö | fi |
| dc.type.ontasot | Master's thesis | en |
| dc.type.ontasot | Diplomityö | fi |