Professional Service Automation : Data classification and profiling from subcontracting point of view
Onikki, Miia-Maarit (2021)
2021
Tietotekniikan DI-ohjelma - Master's Programme in Information Technology
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2021-07-06
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202107016167
https://urn.fi/URN:NBN:fi:tuni-202107016167
Tiivistelmä
This thesis concentrated on classification and profiling of information from subcontractor point of view. The primary goal was to find an answer to the question How should information be categorized and profiled in a new profession service automation system, so that subcontractors can get only needed information to do their daily work? In addition, aim is to define level where does the business risk taking capacity goes between usability and confidentiality?
Used research method was design science research method. It is design method based on definition and analysis of alternative solutions. I started data collection with qualitative interviews and capabilities of the new PSA system. Unfortunately, during the design phase, I was not able to test or investigate very detailed level of the new system. Instead of that, I analyzed collected data from the current and coming system based on interviews and made improvement proposals for M-Files how to profile and share data to subcontractors. I used risk management method for searching the level of the criticality of sharing data.
Main results were new proposal for confidential classification of subcontracting data, impact analysis of most urgent risks and proposal for mandatory key factors for ensuring success delivery of the projects. According to the risk analysis, all money related data like budget, cost, invoices are most sensitive information. It needs to be ensured that visibility of those is locked from the subcontractors. Invoicing and budget planning needs to be done by M-Files internal employee instead of subcontractor. Delivery Item is the riskiest data because it includes several data in metadata card. Restriction of certain data are needed like money related data. Accounts and opportunities need to be restricted also from subcontractors. Those will be shared only need basis, because subcontractors can try to enlarge their own customer portfolio based on the information they receive.
All the other individual data are not so risky to share, but by combining individual knowledge, the subcontractor can get her/him hands on valuable information. More confidential the information, the more precise it must be in terms of information sharing. The conclusion was that finding and determining the exact risk level was difficult. Individual information and its sharing do not yet pose a very high risk, but providing more information and by combining those, there might be higher risk to provide business benefits to other companies.
Used research method was design science research method. It is design method based on definition and analysis of alternative solutions. I started data collection with qualitative interviews and capabilities of the new PSA system. Unfortunately, during the design phase, I was not able to test or investigate very detailed level of the new system. Instead of that, I analyzed collected data from the current and coming system based on interviews and made improvement proposals for M-Files how to profile and share data to subcontractors. I used risk management method for searching the level of the criticality of sharing data.
Main results were new proposal for confidential classification of subcontracting data, impact analysis of most urgent risks and proposal for mandatory key factors for ensuring success delivery of the projects. According to the risk analysis, all money related data like budget, cost, invoices are most sensitive information. It needs to be ensured that visibility of those is locked from the subcontractors. Invoicing and budget planning needs to be done by M-Files internal employee instead of subcontractor. Delivery Item is the riskiest data because it includes several data in metadata card. Restriction of certain data are needed like money related data. Accounts and opportunities need to be restricted also from subcontractors. Those will be shared only need basis, because subcontractors can try to enlarge their own customer portfolio based on the information they receive.
All the other individual data are not so risky to share, but by combining individual knowledge, the subcontractor can get her/him hands on valuable information. More confidential the information, the more precise it must be in terms of information sharing. The conclusion was that finding and determining the exact risk level was difficult. Individual information and its sharing do not yet pose a very high risk, but providing more information and by combining those, there might be higher risk to provide business benefits to other companies.