Big Data Projects are Trickling Down
Big Data is not just for IBM. Many organizations with important requirements are also benefiting from Big Data projects to improve the quality of their products and services, detect and take advantage of new business opportunities and accelerate decision making with fewer errors.
Earlier this year, Dell Software released a study conducted by Competitive Edge Research Reports, a subsidiary of Triangle Publishing Services Co., on Big Data projects and planning. The study, “BIG DATA: Midmarket Companies See Early Success,” concludes that even medium-size firms are now able and eager to benefit from Big Data initiatives.
The report’s key take-home messages could easily apply to Augmented Reality projects in the same and other enterprises. First, Augmented Reality is not just for large organizations.
Second, the report makes a recommendation for Big Data and AR project advocates, regardless of the size of the organization: visionaries who want to use data to change their businesses must have strong senior management as well as IT department support to succeed.
A closer look at their words of wisdom also bear out the need for IT departments to partner with those who ask for big technology investments to make sure they are targeting outcomes that will push business forward.
Lessons Learned
Partnership and collaboration are important in any business, but this study reveals that for big, unproven IT projects, the support and collaboration of senior executive stakeholders is critical to success. Executives have to be willing to go to bat for the best team, to obtain financial resources and data access and to make changes in their businesses to take full advantage of the project’s outcomes.
Another key to success related to the first is for the project to use real time data acquisition and analytics to improve business performance. For some that means making an organization more agile and responsive to its customers. For others, performance is measured in improved product quality (and error reduction). Prototypes and projects in development do not show the great benefits that can come about once technologies are fully deployed and embraced. Once Big Data projects are in production, respondents report significant improvement in key business intelligence metrics. Cost reduction justifications were not among the top six metrics.
There is definitely a lot to learn when designing and putting in place Big Data projects. Much of the necessary talent for complex big data project success can be sourced from within an organization, the study revealed. The respondents said that investing in staff—both to bring specialists in-house when needed and to train existing employees—was quickly justified over outsourcing parts or all of these projects.
The Big Data study participants said they could do more and recommended that others following their steps invest deeply in five enabling technology groups:
- Real time processing
- Predictive analytics
- Data cleansing
- Data dashboards
- Visualization
AR-enabling business systems will improve data acquisition speed and quality, potentially reducing the need for data cleansing and real time data visualization.
Learning from Others
In this study, 300 executives in companies with 2,000 to 5,000 employees shared how they are implementing data-driven approaches to decision making processes. Though not the focus of the study, some decisions must be made with physical world objects and are often taken by people lacking the time and skills to request or perform data analyses. The data on which to base decisions needs to be readily available and meaningfully communicated if it is going to be useful. That is where AR-assisted systems become important.
AREA charter members are reducing the roadblocks to Augmented Reality introduction in their organizations through appropriate collaboration with their IT groups. They are also sharing lessons learned in their projects with one another. Lessons documented in the Competitive Edge Big Data study fit Augmented Reality projects perfectly and there are probably many more Big Data project lessons that will guide enterprise AR project leaders in the future.
Have you been speaking with the Big Data advocates and project leaders in your organizations? What lessons have they shared with you?
Big data does not solve all problems in an organization. There are many myths that should be examined more carefully before selling these to your senior management. Read this article about Gartner Group’s view on big data myths.