Principal topic
This paper is direct the focus on the potential of employees to contribute to innovation, regardless their position in the company – a practice and research stream we know as employee driven innovation (EDI) (Kristiansen & Bloch‐Poulsen, 2010). More specifically, we study the effects of using an online platform to motivate and track employee driven activities. We use a unique dataset of close to 500 employee driven activities responding to the overall strategic goals of a large pharmaceutical retail chain in Sweden.
It goes without saying that expertise, experience, ideas, creativity and skills among employees are valuable resources in the company’s innovation work (Høyrup, 2010) and support achievement of competitive advantages (Kesting & Parm Ulhøi, 2010). EDI include acting on your own ideas and not only respond to needs of the organization (Lovén, 2013), furthermore EDI includes both bottom‐up and top‐down perspectives on innovation (Høyrup, Bonnafous‐Boucher, Hasse, Lotz, & Møller, 2012). The presence of EDI is dependent on mechanisms that influence the organisation’s innovation capabilities (Kesting & Parm Ulhøi, 2010). Dominant mechanisms include fundamental determinants of work engagement known from motivational research, such as the need for autonomy, competence and relatedness (Hakanen & Roodt, 2010; Mauno, Kinnunen, & Ruokolainen, 2007) but also feedback and the possibility of seeing one’s own part in the bigger picture (Hackman & Oldham, 1980).
Amundsen et al. (2014) who suggest that important factors for stimulating EDI include leader support through the generation, registration, evaluation and realisation of ideas; a collaborative climate including interactions between colleagues and between employees and external contacts; rendering autonomy and delegation of decision‐making authority to employees. Research has also highlighted several restraining forces for EDI, such as the gap between management and employees and the fact that managers are not capable of seeing the things that employees meet in their daily work (Kesting & Parm Ulhøi, 2010).
Despite the vast knowledge relating to motivational theory, social comparison and social facilitation surprisingly few studies examine how this knowledge could be combined and successfully be put to practice to promote EDI. The focus on the majority of work has been on investigating restraining and enabling factors of EDI (Aaltonen & Hytti, 2014; Kesting & Parm Ulhøi, 2010), exploring how EDI occurs in teams (Kristiansen & Bloch‐Poulsen, 2010) and small organizations (Aaltonen & Hytti, 2014). As a result of this, we know a lot about what need to be accomplished to promote EDI, but we do not know what tools work or not to reach those accomplishments. In particular, we know little about how this could take place in large organizations where people are spread geographically.
By drawing upon knowledge from social cognitive theory (Bandura, 2001) showing that strong perceived collective efficacy increase people’s aspirations and motivations, we analyze the outcomes from a year-long strategic work at a large pharmaceutical retail chain in Sweden. This takes shape in a database consisting of detailed information on close to 500 employee-driven activities in a large pharmaceutical retail chain in Sweden. Social cognitive theory extends the conception of human agency to collective agency (Bandura 1997) where people’s shared belief in their collective power is a key ingredient
Method
We use a unique data set of close to 500 employee-driven activities entered in a cloud-based, online database. The database was used as a means to active the employees at the 370 retail units in an organizational change project launched earlier the same year. The project started off with 32 physical dialogue meetings between the CEO and the retail unit staff where the overall strategic goals were presented and discussed. Ambassadors in management positions were appointed at each retail unit, responsible to encourage, initiate and document the activities rendered by the employees. The online database allowed for constant transparency between the retail units – giving the possibility to share ones ideas and experiences, mistakes and successes throughout the whole year while the project was running. The database consist of secondary data, as we did not intervene in the creation or execution of the project. Same thing goes for the written evaluation made after the project was completed – where employees were asked about their impressions and experiences from using the database.
The retailing business is highly competitive and the geographical spread of employees makes it a suitable context to explore the use of online tools of this kind for promoting EDI in other large businesses or smaller businesses geographically spread.
We used mainly qualitative analysis methods to explore the database as well as simple quantitative analysis to produce frequencies and descriptive data. By coding each activity according to the degree of innovativeness and type of activity (e.g. internal process, customer service) we could form a good understanding of the outcomes from using the database.
Results and implications
Our study of the database and the subsequent employee evaluation form reveals interesting and uplifting results. For example, 64 % said the online tool helped them better understand the overall strategy and 85 % were happy with the user interface and continuous work with the tool. Also, half of the retail outlets claimed the tool helped them run projects which increased sales considerably. Among the more successful activities were one initiating earlier opening hours (which previously was attempted to be pushed up-down without success) – this activity alone corresponded to the average turnover of 22 outlets.
The result are in line with social comparison and social facilitation theory, showing how public praise and social comparison seem to improve employee driven innovation motivation (Mumm and Mutlu (2001). Although comparative studies are hard to find (we did not) similar findings were made in the use of mobile exercise applications. A recent study by Hamari and Koivisto, 2015) shows that social influence, positive recognition and reciprocity have a positive impact on how much people are willing to exercise. In fact, the more “friends” a user the larger the effects were, which could explain the success of the online tool in this study – which involved the exposure among more than 300 outlets. Our findings, similar to Hamari and Koivisto (2015), further our understanding on the phenomenon of social influence showing, how public recognition and network effects contribute to the collective employee-driven innovation.