Instruments of Change: Professionals Achieving Success Through Operation-Specific Digital Transformation
Digital transformation has become a buzz-phrase of epic proportion and typically means a sweeping order from the top-down to change the entire digital strategy of the company. Employees at every level are expected to carry the load despite the realities of how it may impact their workflows. For years, this top-down methodology has remained the default approach, despite its pervasive cost and implementation issues. According to our new report, an upsurge of professionals are testing a better strategy: one change to a specific task, one program to solve one problem. Op-Specific Digital Transformation allows organizations to digitize a specific task or workflow in a professional’s direct responsibility. This method is highly focused on successfully digitizing one operation, instead of gambling the chance at improving everything all at once. Our new report explores this approach, and why so many professionals are adopting this method.
Breaking Ground on Implementing AI: Instituting Strategic AI Programs – Moving from Promise to Productivity
While manufacturing companies see the value in implementing Artificial Intelligence (AI) solutions, many are struggling to deliver clear results and are reevaluating their strategy, according to our new report. To gauge the progress and process of how manufacturing companies are implementing AI and whether or not they are satisfied with their AI initiatives, we surveyed 250 manufacturing professionals in October 2019 with visibility into their company’s AI programs. The findings revealed that almost two-thirds (61%) of manufacturing companies said they need to reevaluate the way they implement AI projects. Key findings from Plutoshift’s report include:
  • 57 percent said their company implemented AI projects with a clear goal, while almost 20 percent implemented AI initiatives due to industry or peer pressure to utilize the technology
  • 17 percent of respondents said their company was in full implementation stage of their AI projects
  • 62 percent said their company took more time than anticipated to acquire internal buy-in and commitment in implementing AI
  • 60 percent said their company struggled to come to a consensus on a focused, practical strategy for implementing AI
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Barriers and Solutions to Surfacing Value from Data in Manufacturing
As remote sensors, connected devices, and software capture a myriad of data on the efficacy of processes and the value of assets, manufacturing professionals are struggling to make sense of what all the data is saying and how to use it to improve their systems. This issue comes at a time when the costs of energy, materials and labor continue to rise and efficiency is paramount. We wanted to examine the issue and see how manufacturers can better utilize the data they are already collecting. We surveyed 500 mid-level manufacturing professionals across industries to examine data collection and value and to understand how to better utilize data for maximum value. Key findings from Plutoshift’s report include:
  • Nearly half (48%) of respondents said their companies use spreadsheets or other manual data entry documents
  • Only 12% of respondents said they take action on their data insights automatically
  • 76% of respondents said in order to take immediate action collected data, they need software solutions that analyze data in real-time
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