It’s not unusual for an organization to have a centralized framework for deploying global analytics. However, according to Gartner more than half of all analytics projects fail. With those kind of statistics you have to ask yourself, “Is there an easier way?” Here at Cervello, we know there is. Cloud technology has brought a lot of opportunities and successes to organizations that are willing to take the leap. Effectively closing that project-failure gap by leveraging the combination of new and innovative cloud technologies, such as Birst, with new organizational approaches to global enterprise analytics projects is key.
Companies struggling to successfully deploy analytics across the global enterprise typically find themselves with solutions that have one or many of the following associated issues:
- Inflexible analytics no one knows how to use or extend
- Data that lacks meaning to be useful to the local and specific business function
- Lack of deep technology expertise to not only support, but extend the tools
Cloud, however, is enabling organizations to remove these roadblocks by successfully delivering global analytics through centralized governance while empowering local insights through a decentralized model. Cloud solutions such as Birst are making this possible by combining new technology and subscription-based models with low barriers to entry and self-service capabilities.
Let’s review three highly impactful areas within business intelligence (BI) programs where innovation via cloud technologies such as Birst are changing the game.
1. Metadata Migrations: With BI systems there are multiple areas where metadata changes can occur, be it at the data extraction, repository, business friendly semantic, or reporting layer. Typically in order to migrate new information from any one of these areas across your environments some downtime would be required or you would need an individual who is extremely well-versed in the technology. With Birst, this is no longer the case. Birst enables you to take any single portion of any one of these layers and migrate them to the next with just a few clicks of a button. No downtime, no engineers, no problem. This one functionality saves countless hours in maintenance and support. Beyond simple maintenance procedures, Birst’s Metadata Migration capability also allows for the creation of an expansive ecosystem for BI. As an example, one of our clients, a global consumer packaged goods company has leveraged this functionality to enable independently-run reporting across 22 countries. Each country (or market) leverages the same governed data model which is maintained in one instance, but proliferated across 22 separate locally managed Birst spaces. Each space has its own data loads, its own metadata loads, and its own locally created report sets that make sense for the market. When the centralized, governed data model is updated with a few clicks, all 22 decentralized, local markets have an updated model with its enhanced capabilities. How is that for governed self-service!
2. Networked Data Warehousing: With Birst, your ability to deliver data to your business users is no longer taken hostage by your team’s inability to quickly build or augment an Enterprise Data Warehouse. The platform has end to end BI capabilities. You can stage, transform, and model your data within Birst. Then Birst’s Automated Data Refinement takes over, building out a star schema as its own central repository. Within each Birst environment you can package up all or portions of that data model / star schema for other teams to subscribe to. This is game-changing flexibility. Imagine being able to model data and share that model with other areas of the business. As an example, perhaps your Finance team has the appropriate definition of your product dimension, containing all the attributes you need to report on while your Marketing team has the list of clients you’ve been looking for. With Birst, you can subscribe to these areas of their data models, and then incorporate them into your own. This allows you to effectively create a networked eco-system in a way that allows the domain data experts within your enterprise to manage the areas they need to manage. Flexibly for the entire organization is essentially enabled without compromising data governance.
3. System Upgrades: With cloud solutions, gone are the days where system upgrades require additional software licensing, development, regression testing, and impactful downtime. When you leverage a cloud solution you typically see upgrades roll automatically through on a quarterly or even monthly basis. No additional costs, downtime, or extensive regression testing by your team is required. In comparison, we’ve seen on premise software upgrades cost in the hundreds of thousands, with zero business upside, and months of planning. It’s safe to say, if your organization is on a legacy enterprise performance management or BI system, the cost and time associated to upgrade activities has always been a roadblock to innovation.
While the technology change may be leading the charge, it’s only the tip of the iceberg. Areas impacted by cloud analytics are not just technology focused. There is also a shift in how organizations handle project management, resourcing, and budgeting for these programs due to new capabilities.
On the project management side, the tried and true Center of Excellence (CoE) approach is one that needs to be revisited for the cloud. Given the flexibility of the Birst platform, it’s wise to build a central framework, but also encourage a decentralized one. For example, the CPG client previously mentioned enables Birst through a centralized CoE, but also has a decentralized team to manage the needs of the core local businesses. This allows the local teams to be aware of the “rules of the road” while supporting the local markets to make updates and enhancements to the system as needed. The central CoE manages the ‘what’ and the ‘how’ for each subject area added to the global business model for analytics. However, the local teams are responsible for ensuring their business model for those subject areas includes the local data sets, attributes, and key business indicators that are appropriate for the region. By leveraging the Birst framework, centralized business model enhancements can be published out to the local models without impacting any of the local customizations. This ensures an appropriate blend of resources, be it people or monetary come into play when augmenting these solutions.
As you can see, it’s an exciting time in cloud BI and analytics. With the innovations provided by cloud solutions such as Birst there are a myriad of new and creative ways to approach old problems. I am amazed by the conversations I have with organizations about their BI initiatives. Cloud is so infrequently discussed, and companies are still contemplating BI and analytics projects in the same way they would approach a legacy BI project. It’s time to start asking different questions. It’s time to realize that although the technology is new we might be trying to solve old problems with the same approach, resulting in the same antiquated or even failed outcomes. It’s time to rethink your BI and enterprise global analytics approach, and leap into the clouds. We promise you will not be disappointed in the results. Of course it also helps to work with a system implementer that has the know-how to guide you along the way.
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