Framework for starting to use big data analytics in companies’ supplier selection

Either of the case companies is not yet utilizing big data analytics in any way in their business processes. They have rather only been curious about the topic and investigated the big data possibilities a bit, but nothing really concrete has happened in the case companies towards starting to actually utilize big data analytics in their supplier risk review and supplier selection processes even though to some extend the both case companies understand the possibilities and benefits of big data anaytics. In this section the thesis suggests a framework or guidelines how companies could possibly prepare themselves to be readier for big data utilization or how they could start to test big data analytics usage in their process of risk review related to supplier selection (Figure 11). The basic core behind the framework is the basic risk management process, where risks are first identified and analysed, then evaluated and treated accordingly (Tummala and Schoenherr, 2011). The correct supplier selection to succeed also demands constant communication, consultation, supplier information gathering, monitoring and reviewing of suppliers as constant side processes.

To use big data analytics with success, it is important to have a structured evolutionary approach to accommodate the big data’s broad scope. Firstly, companies should start to use their internal data to have a clearer picture of data sources that would benefit the company so the company can go and expand to external sources. What is more important than the data amount is to have an integrated data analysis process. Taking small steps in implementing big data systems allow companies to identify areas of weaknesses and risks. (Meraglim, 2017) Companies should also select judiciously the situations in which they start to exploit big data and not to invest and integrate big data into everything they do but rather test it first with some operations that are most suitable for the big data analytics usage and would benefit most of it. Further there is a great myriad of challenges related to big data and especially in the utilization of it in the

business processes. All of these challenges should be identified and analyzed before starting any big data activity in the case companies as they could generate resistance towards big data analytics within the employees if they are not first handled.

Figure 11. Framework for starting to use big data in companies’ supplier selection and risk management processes

First and foremost, it is important to have a vision in the companies for example that big data will be made into a competitive advantage and make concrete objectives for big data usage. The companies need to change their mindset they have about big data

and strive to be more data-oriented and have an open attitude towards big data utilization. The vision should be concrete, limited in time, understandable, realistic and inspirational for it to work. Companies should have a desire to use all the accessible data and to see this as a possibility and not as a threat. What is also important is to determine big data from the view point of what it means to the company, what the company wants to achieve with it and what are the companies’ objectives of big data usage. The benefits of big data usage need to be made visible and concrete to everyone in the company’s supply chain – the company itself, its customers and suppliers.

The next step after achieving the shared vision and attitude towards big data throughout the company would be strategy planning and execution based on the objectives set. However strategy is something that many enterprises lack when it comes to big data utilization. Still planning the strategy how to start big data related operations in their organizations’ processes is a very important step for companies planning big data analytics utilization. The whole company should take a part in big data strategy. Also for the implementation to work the process should start from the top to the bottom – the top management needs to be committed to the change. To help in this companies could have consults or other big data experts on board who would explain the benefits, possibilities and provide training. Companies also need to make room for big data analytics processes to ensure the open information sharing that is needed for big data analytics usage to succeed. What is also needed is all the needed resources for big data analytics usage and training for employees.

One example to start big data operations is to first have some concentrated smaller group who starts investigating and deploying big data analytics usage in companies’

business operations little by little. This group would have the responsibility to gather all the needed resources companies need for big data analytics usage and provide training to employees. Later these people would also be the ultimate big data responsible people in the company’s processes utilizing big data. Companies could have one person in every project that could be the so called big data responsible who would help in getting needed information for risk management and supplier selection process. After that companies could slowly integrate big data analytics usage to the whole organization if needed and seen even necessary. What needs to be noted is that companies might have to harmonize their nomenclature they use in all of their business operations and in some areas they might need to harmonize the whole process to be able to gather information effectively and to be able to utilize big data in supplier selection. Thus harmonizing the whole process is a huge task to complete. To

conclude big data analytics utilization brings value to the whole process of supplier risk review related supplier selection and ensures the correct supplier selection.