In 2014, analytics implementations will be put under further scrutiny, and leaders will be looking to increase its use to ensure cost-savings and efficiencies meet, and exceed their target where possible. Organizations will also have one eye on the future, and how best to embrace and utilize analytics in a more predictive manner.
Predictive analytics will move further up the C-suite agenda in 2014. As many organizations have descriptive analytics in place, they will be looking to build on this and look to use these tools and data for predictive analytics, and eventually to start to proactively provide options for future decisions (prescriptive analytics). With Gartner estimating that those using predictive business performance metrics will increase profitability by 20% by 2017, there will be pressure to implement predictive metrics. Organizations must ensure that they have the sufficient foundations to be able to integrate, cleanse and enrich their data to ensure that any predictive - and even prescriptive - analytics is accurate as possible.
Many organizations have implemented analytics, but are struggling to see any value being added as insufficient training (either initially or an ongoing basis) is given to users to get the most out of it.
With specific Big Data expertise being an unavailable and expensive resource for many, the focus should rightly switch to how to most effectively enable the wider workforce to use data and analytics as part of their everyday decisions – making data the domain of the many rather than the chosen few.
For this to happen effectively, organizations need training strategies in place to support the ongoing education and development of their users. Without this, it will be impossible for organizations to effectively expand their analytics initiatives.
As cloud adoption accelerates in 2014, so will concerns about data governance, risk and resilience, with 90% citing data access and protection as extremely or very important security capabilities. Vendors will be put under scrutiny to ensure that they are up to the challenge and allay data privacy and security fears.
The project-based nature of cloud deployments will be used by organizations as a way to test the cloud in a risk-free way. We’ve found that questions relating to security and governance are increasing from clients and prospects, and that more and more are looking towards certifications such as ISO 27001:2005 for Information Security Management as being a critical part of any vendor review.
Cost will continue to be high on the corporate agenda, and there will be renewed emphasis on ways to do more with less – with many looking to integrate data management, analytics and BI capabilities via a single, cloud-based platform.
Focus will transfer to the cloud to provide savings in terms of deployment time, flexibility and providing a suite of tools within a single, scalable low-risk solution such as the RAPid platform.
A cornerstone of analytics success in 2014 will be an organization’s ability to successfully identify the key data and metrics for analysis. The issue for many is the speed at which this can be done.
In a recent study, IDG research found that the primary driver for Big Data initiatives for 53% of respondents was the ability to make faster business decisions. In the same report, IDG found that 42% have experienced a loss of business occasionally or frequently due to an inability to quickly find sought-after information; showing just how speed really is of the essence for analytics.
With multiple data siloes, it takes time to access the right data for analysis. The most effective way to overcome this is to break down the siloes in which data currently exists, and integrate, cleanse and enrich, to provide one cohesive platform for use. Users then have a single view of data, accessed quickly, which can then be sliced and diced according to specific business need or desired outcome, resulting in analytics deployments being much more efficient, effective and aligned to business strategies.
If you haven't already had a chance to take a look, you may be interested in reading Part 1 of our 2014 Predictions for data management and analytics.