Implementations of new technologies including artificial intelligence and Internet of Things continue to focus on simple projects that deliver quick returns based on streamlining internal processes, neglecting the truly transformational opportunities presented.
Transforma Insights published its latest case study insight report entitled ‘digital transformation Implementation Best Practice’ which uses analysis of over 600 real-world digital transformation (DX) deployments to provide enterprises with best practice on how they should be thinking about using new technologies.
The key findings are:
Most organisations are hesitant to extend beyond relatively safe deployments focused solely or predominantly on simple efficiency savings. Over 70% of projects can be considered to have a significant impact on process efficiency. In contrast less than 30% have significant impact on the organisation’s products and services, and barely 10% are potentially disruptive to the industry as a whole.
Further supporting the idea that enterprises are playing it safe, only 24% of projects can be categorised as ‘mission critical’, although that figure rises to 68% for robotic process automation (RPA), which is generally the most mature and well understood of the technologies.
Given the focus on easy wins, it is unsurprising that the emphasis is generally on deployments that are quick to deploy and pay back. On average projects take 12 months, with payback in 20 months, although there are some outliers. RPA is substantially slower to deploy, reflecting the fact that its is being used more comprehensively, and PLM slower to generate a payback, as illustrated in the chart below.
The study also examined three measures of the complexity of implementations: functional (i.e. how complex the project is), stakeholder (i.e. the number of internal and external stakeholders in a project), and geographical scale (i.e. how many countries it is deployed in). No single technology family ranked as typically being complex in more than one category. This implies that complexity in one area limits the capacity to accept complexity in any other.
Some technology families (including autonomous robotic systems) are more given to productised solutions. Others require a high degree of customisation (including Distributed Ledger) reflecting maturity of both buyers and sellers.
Jim Morrish, founding partner at Transforma Insights commented: “The most startling thing is the continued immaturity of almost all of the technology sectors that we examine. With the honourable exception of robotic process automation, every other category suffers from deployments that err on the side of playing it safe. Of course, there’s a lot of value in grabbing the low-hanging fruit, but we should have got past that stage with many of these technology families, particularly Internet of Things. The lack of ambition implies that there’s a lot more potential yet to come.”
This study is based on analysis by Transforma Insights of hundreds of digital transformation implementations around the world. The team of expert analysts assessed each implementation and calibrated it against 250 solution characteristics with the aim of better understanding the prevailing trends in technology deployment and to extrapolate best practice.
Commenting on the research, Founding partner at Transforma Insights Matt Hatton said: “This is the most comprehensive categorisation and analysis of real-world new technology developments that we’ve ever seen. It’s one thing to hypothesise about how organisations are deploying AI, IoT, RPA and other technologies, but it’s quite another to dig deep to find out exactly what has been happening. The results are striking.”
About our research
Our analysis of real-world deployments provides an unrivalled database of technology implementations, which can be accessed via our Best practice & vendor selection database.
It also allows us to perform analysis comparing the deployment characteristics and motivations between the different digital transformation technologies. That is the focus of this report.
This report includes analysis of ten of our twelve technology families: artificial intelligence, autonomous robotic systems, data sharing, distributed ledger, human machine interface, hyperconnectivity, Internet of Things, product lifecycle management and robotic process automation.
Analysis of each technology family’s case studies can be found in the Technology Insight Reports available on our Reports page.
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