Innovation and Technology
Enterprises Struggle to Implement AI
AI is a Journey
A Journey of Four Stages
If you worry that your organization is falling behind in its artificial intelligence initiatives, don’t feel so bad — just about everyone is still in the learning and piloting stages. And if it’s unclear whether there will be return on investment at the end of all this work, there is financial advantage as well, research out of MIT finds.
The Four Stages of AI Advancement
According to an analysis of 721 companies by the MIT Center for Information System Research (CISR), there are at least four logical stages in AI advancement. Most enterprises are still working through the experimental and pilot stages.
Stage 1: Experiment and Prepare (28% of organizations)
In this stage, enterprises focus on educating their workforce, formulating AI policies, becoming more evidence-based, and experimenting with AI technologies to grow more comfortable with automated decision-making. Company leaders start taking a look at how to address concerns such as ethics and skills to ensure a smooth path forward.
Stage 2: Build Pilots and Capabilities (34%)
At this stage, proponents “define important metrics, begin to simplify and automate business processes, and develop the enterprise capabilities they’ve learned.” At this stage, use cases are piloted, with work on leveraging enterprise data and developing APIs. Work with large language models also commences at this stage.
Stage 3: Develop AI-Driven Ways of Working (31%)
At this stage, AI essentially becomes industrialized, meaning it is available and replicable across the enterprise. This includes work on building a core platform for AI, ensuring transparency to decision-makers via dashboards, and ultimately transforming the organizational culture to encourage data-driven and innovative thinking. Foundation models and small language models are introduced and applied to enterprise opportunities.
Stage 4: Become AI Future Ready (7%)
At this achievement stage, “AI is embedded in all decision-making throughout the enterprise,” the researchers state. “They leverage proprietary AI internally, and many sell new business services based on this capability, the AI capability as a service, or both to other enterprises.”
Financial Advantage
The research out of MIT finds that enterprises in stages three and four have financial performance well above industry average — exceeding 10 percentage points. In fact, companies in Stage 4 averaged 10.4 percentage points above the industry average.
Conclusion
Successfully moving through these stages of AI growth requires a cross-enterprise collaborative effort, as the technology can recast and accelerate many parts of the enterprise. One thing is clear; AI success is a journey, and the ability to rapidly leverage and adapt resources and technology is key — as new technologies and capabilities keep arising almost every day.
FAQs
* What are the four stages of AI advancement?
+ Stage 1: Experiment and Prepare
+ Stage 2: Build Pilots and Capabilities
+ Stage 3: Develop AI-Driven Ways of Working
+ Stage 4: Become AI Future Ready
* What is the financial advantage of AI advancement?
+ Enterprises in stages three and four have financial performance well above industry average — exceeding 10 percentage points.
* How many organizations are in each stage?
+ Stage 1: 28%
+ Stage 2: 34%
+ Stage 3: 31%
+ Stage 4: 7%
Innovation and Technology
Rebranding the Corporation
Reinventing Innovation
The Idea in Practice
Research Principles
1. Study “technology in use” to improve work processes. PARC customizes behind-the-scenes information technology to enhance work practices and “listen” to customers.
A new software feature on Xerox’s high-end copiers predicts machine breakdowns, calls a branch office to download its predication, and schedules a repair person to visit the site—before the expected breakdown. Customers never see a machine fail, and Xerox uses information generated by the software to design future generations of copiers.
2. Harvest local innovations. Most employees constantly improvise to handle surprises and solve problems. But these “workarounds” rarely spread beyond their local groups to benefit the larger organization. PARC’s solutions? One is easy-to-use programming tools enabling employees to disseminate knowledge throughout the company. Another is revamped training methods to increase organizational learning.
After realizing that Xerox’s service reps learn more by swapping stories than through formal training, PARC began envisioning a multimedia information system—filled with annotated videoclips of useful stories that would let reps from around the world plug into Xerox’s collective memory and learn from past successes and failures.
3. “Coproduce” new technologies and work practices with partners throughout your company. To communicate new insights so that others in your company can grasp their potential, don’t simply pour knowledge into their heads. Instead, help them develop whole new mental models.
With the advent of digital copying, Xerox had to challenge long-held assumptions about products, markets, and customer needs that the older, light-lens xerography had created. Before building the technology, PARC helped managers think about copiers in fresh ways. It created a video in which researchers acted out the new technology’s potential, then challenged viewers to imagine additional uses for digital copying.
4. Innovate with customers. Research’s ultimate partner? The customer. Collaborate with customers to co-produce technology and work systems they’ll need in the future.
Xerox’s pharmaceutical customer, Syntex, wanted to better manage the 300,000+ drug-test report forms it collects annually. Through Xerox’s Express project team, Syntex employees spent time at PARC learning about Xerox’s technologies-in-progress. PARC researchers, engineers, and marketers observed them in action at Syntex. Results? A new document-management system that solved Syntex’s problem and became a prototype with potential value for the entire pharmaceutical industry.
Conclusion
To prevail amid rapid and unpredictable change, your company must do more than simply invent new technologies and breakthrough products. It must reinvent the innovation process itself. By designing cutting-edge work processes that enable your organization to innovate continuously, your research department can reinvent your corporation.
FAQs
Q: What are the four powerful principles to reinvent the innovation process?
A: Study “technology in use” to improve work processes, harvest local innovations, “coproduce” new technologies and work practices with partners, and innovate with customers.
Q: How can we improve our work processes using technology?
A: By customizing behind-the-scenes information technology to enhance work practices and “listen” to customers.
Q: How can we spread innovative solutions across our organization?
A: By using easy-to-use programming tools to enable employees to disseminate knowledge throughout the company and revamped training methods to increase organizational learning.
Innovation and Technology
36TB HAMR
Seagate Mozaic 3+ Hard Disk Drive
New Shipment of Exos M Hard Disk Drives
Seagate Technology has announced the shipment of Exos M hard disk drives, HDDs, with up to 36TB storage capacity to customers. These HDDs utilize Seagate’s Mozaic 3+ heat-assisted magnetic recording, HAMR, technology, which employs lasers to reduce the magnetic fields from the write head required to write high-densities on stable high coercivity magnetic recording media.
Increased Storage Capacity and Areal Density
The 36TB HDDs feature 10 disks, providing 3.6TB per disk. This likely results in about 1.8TB per square inch areal density, a 13% advance over the prior 32TB HDDs. The chart below shows Coughlin Associates’ history of shipping HDD areal densities.
Hard Disk Drive Product Areal Density Growth History
[Coughlin Associates]
Seagate projects that 10TB per disk is attainable, enabling a 100TB 10-disk HDD. This trend indicates that HAMR allows HDD areal density growth, and thus the increased capacity per HDD, could grow as much as 15-20% annually.
Data Center Storage Advantages
Seagate claims that these drives will provide significant advantages for data center storage, including scale, total cost of ownership, and sustainability. The company says that these drives can provide 300% more storage capacity within the same data center footprint, a 25% cost reduction per TB, and 60% power reduction per TB compared to prior generation products.
AI-Driven Storage Demand
A Recon Analytics survey, commissioned by Seagate and conducted in November 2024 with 1,062 participants, showed some interesting trends on how AI is creating increased digital storage demand. The survey found that:
* 61% of infrastructure buyers who predominantly use cloud storage for AI data management expect storage requirements to at least double by 2028 due to retention times increasing from 6 months to forever.
* 73% of respondents using daily or weekly LLM checkpointing.
* 80% deeming data replication for AI very or moderately important.
* 95% of storage buyers using AI or planning to adopt it are taking measures to accommodate the growing storage requirements.
Conclusion
Seagate’s Exos M hard disk drives with Mozaic 3+ technology offer significant advantages for data center storage, including increased storage capacity, power savings, and cost reductions. The growing demand for storage driven by AI adoption highlights the importance of cost-effective storage solutions like HDDs.
FAQs
Q: What is the storage capacity of Seagate’s Exos M hard disk drives?
A: The storage capacity of Seagate’s Exos M hard disk drives ranges from 32TB to 36TB.
Q: What is HAMR technology?
A: HAMR technology is a heat-assisted magnetic recording technology that employs lasers to reduce the magnetic fields from the write head required to write high-densities on stable high coercivity magnetic recording media.
Q: What are the advantages of Seagate’s Exos M hard disk drives for data center storage?
A: The advantages of Seagate’s Exos M hard disk drives for data center storage include scale, total cost of ownership, and sustainability. These drives can provide 300% more storage capacity within the same data center footprint, a 25% cost reduction per TB, and 60% power reduction per TB compared to prior generation products.
Innovation and Technology
The Power of Data Analytics: How to Optimize Workflows and Boost Productivity
Innovations in Workforce Productivity
In today’s fast-paced and competitive business landscape, the ability to optimize workflows and boost productivity is more crucial than ever. With the constant influx of data, businesses are facing challenges in managing their workflows, managing resources, and making informed decisions. This is where data analytics comes in, providing valuable insights to help businesses streamline their processes, improve efficiency, and ultimately, drive success.
The Benefits of Data Analytics
Data analytics offers numerous benefits to businesses, including:
-
Improved Decision-Making
Data analytics enables businesses to make informed decisions based on facts, rather than gut feelings or intuition. By analyzing data, businesses can identify patterns, trends, and correlations that can inform strategic decisions.
-
Enhanced Process Efficiency
Data analytics helps businesses to identify bottlenecks and areas of inefficiency, allowing them to optimize workflows and streamline processes.
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Better Resource Allocation
Data analytics provides valuable insights into resource allocation, helping businesses to prioritize tasks and allocate resources effectively.
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Increased Productivity
Data analytics enables businesses to identify areas of inefficiency and waste, allowing them to streamline processes and reduce unnecessary tasks, ultimately leading to increased productivity.
How to Optimize Workflows with Data Analytics
So, how can businesses optimize workflows and boost productivity with data analytics? Here are some tips:
-
Define Key Performance Indicators (KPIs)
Identify the most critical metrics that affect your business’s success and use data analytics to track and analyze them.
-
Collect and Analyze Data
Gather data from various sources and analyze it using data analytics tools to identify patterns, trends, and correlations.
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Visualize Data
Use data visualization tools to present data in a clear and concise manner, making it easier to identify areas of improvement.
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Make Data-Driven Decisions
Use data insights to inform business decisions, rather than relying on intuition or guesswork.
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Monitor and Adjust
Continuously monitor the performance of your business and adjust processes as needed based on data insights.
Tools and Technologies
There are numerous tools and technologies available for data analytics, including:
-
Spreadsheets
Spreadsheets like Microsoft Excel and Google Sheets are great for data analysis and visualization.
-
Data Visualization Tools
Tools like Tableau, Power BI, and D3.js are ideal for presenting data in a clear and concise manner.
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Data Science Platforms
Platforms like Python, R, and Apache Spark are popular for data science and machine learning tasks.
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Cloud-Based Analytics
Cloud-based analytics platforms like Amazon Web Services (AWS) and Google Cloud Platform (GCP) offer scalability and flexibility.
Challenges and Best Practices
While data analytics offers numerous benefits, there are also challenges to overcome, including:
-
Data Quality
Ensuring the quality and integrity of data is crucial for accurate analysis and insights.
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Data Volume
Managing large volumes of data can be overwhelming, but data analytics platforms can help alleviate this challenge.
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Lack of Skills
Some businesses may lack the skills and expertise needed to analyze data effectively, making it essential to invest in employee training and development.
-
Data Security
Protecting sensitive data from unauthorized access or breaches is essential, making it crucial to invest in data security measures.
Conclusion
In conclusion, data analytics is a powerful tool that can help businesses optimize workflows and boost productivity. By leveraging data analytics, businesses can make informed decisions, improve process efficiency, and ultimately, drive success. Remember to define KPIs, collect and analyze data, visualize data, make data-driven decisions, and monitor and adjust processes as needed. With the right tools, technologies, and best practices in place, your business can thrive in today’s fast-paced and competitive business landscape.
FAQs
What is data analytics?
Data analytics is the process of extracting insights and value from data using various techniques and tools.
What are the benefits of data analytics?
Data analytics offers numerous benefits, including improved decision-making, enhanced process efficiency, better resource allocation, and increased productivity.
How do I get started with data analytics?
Start by defining your business’s key performance indicators (KPIs) and collecting relevant data. Use data analytics tools and technologies to analyze and visualize the data, and make informed decisions based on the insights gained.
What are the challenges of data analytics?
Common challenges include data quality, data volume, lack of skills, and data security.
What are the best practices for data analytics?
Best practices include defining KPIs, collecting and analyzing data, visualizing data, making data-driven decisions, and monitoring and adjusting processes as needed.
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