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INTRODUCTION
Why is digital transformation (DT) so hard? 70% of digital transformation initiatives fail (Tabrizi et al., 2019). Moreover, research firms like Garner predict the rate of failure of a digital transformation project to be higher than those of classic IT projects, with only a 15% success rate (Gartner, 2018). Field observations show that too few companies have the leadership capabilities to make digital transformation a success. A study in the finance industry reveals that 77% of firms deploying digital transformation solutions have not obtained the expected results (Sparks, 2018). Buvat et al., (2018) found that 65% of businesses believe they do not have the right leadership abilities to succeed in their digital transformation journey.
This paper intends to identify key success factors at each of the critical phases of a digital transformation initiative to allow existing firms to leverage the value creation potential of digital transformation successfully. In this research, we focused on DT aimed at improving forecasting and order placement using which is broadly called artificial intelligence (AI), a subset of DT using large sets of data to recognize patterns to allow computer systems to make autonomous recommendations (Helm et al., 2020; Niessing & Ho, 2020). In the supply chain, its purpose is often to deliver more accurate order planning and management.
Hence, the research question is: “Beyond technology elements, what are the key success factors at the main stage of a digital transformation initiative”.
LITERATURE
What is Digital Transformation?
Digital transformation (DT) is broadly defined as a transformation undergone by firms that adopt data-driven innovation to create more value for the firm and its stakeholders, altering business processes, products, services, relationships (Morakanyane et al., 2017; Osmundsen et al., 2018; Verhoef et al., 2021). DT encompasses multiple technologies and processes around the collection of data, its analysis, and the extraction of value (Magistretti et al., 2019).
The drivers for AI-based transformation are either external pressures, either opportunities to improve offer or react to competitive threats, or internal, increase efficiency and enable organization leverage (Loonam et al., 2018). Considering the far-reaching impact, and often the significant resource commitment of developing a digital-driven business model, the initiatives are usually driven at the C-Suite level, by the CIO or the CEO. Unfortunately, both CIO and CEO often admit to having only a superficial understanding of the challenges (Solis, 2019).
Firms that have mastered the implementation of DT have achieved significant benefits, becoming more agile, more profitable, and improving their offer, as well as capitalizing on digital innovation for their sustainable business growth (Dash et al., 2019; Sultana et al., 2021). These pioneering firms have already seen the results of their first projects and are now set to make their business model evolve, widening the gap with the followers. They have understood that the key success factor is to focus on competitive dynamics rather than cost optimization” (Ransbotham et al., 2019). For the firms that successfully overcome the transformation challenges, the benefits of DT is forecast to increase by 10% to 100% in most industries (Bughin et al., 2019; Purdy et al., 2017).