It is a fact of life that organizations need to upgrade NMS, CIS, MDM and other large systems to keep pace with vendor changes. This paper will discuss why implementing Oracle Utility Analytics (OUA) simultaneously with a source system upgrade is not only possible, but represents best practices for both source system and analytics implementations.
Using Oracle Utilities NMS as an example, here’s why your next upgrade project should include simultaneous implementation of prepackaged analytics along with the source system:
Organizations upgrade NMS systems to take advantage of new functionality and to stay current with changes in technology. The cost of such projects can be significant and take over a year to finish. Planning involves both functional and technical resources whose time needs to be coordinated. New requirements must be collected. Funds must be procured. Upcoming business and legal requirements need to be predicted and collected.
But even with all of this – and partly because of it – we have seen that an NMS upgrade project is the ideal time to implement or upgrade OUA. At first, this notion may sound counterintuitive; adding more scope to a large project seems like it adds to the likelihood of failure and clearly adds to the amount of money the organization must spend.
So let’s look at this issue from these viewpoints:
Delivering both the NMS upgrade along with the accompanying OUA for NMS together can be done in almost no extra time compared to an NMS upgrade on its own.
In planning and executing an NMS upgrade together with an OUA implementation, the organization will do a single fit gap analysis and focus reporting requirements on the reporting system, not spend time crafting a temporary stop gap solution or attempting to retrofit the old reporting solution onto the newly upgraded NMS system. Either of these could result in suboptimal results and duplicated effort.
Organizations do a lot of reporting against their NMS systems. Especially during storms, real time data is critical, and a correctly implemented OUA installation excels at providing near-real-time information without putting additional strain and degrading performance of the NMS system. And the fact is that much reporting can be done without up-to-the-minute data with no loss in value. The BI tools in OUA are far easier to use for data exploration and to build reports than running queries against the NMS source system, and there will be no impact on performance. Several reports can be combined into one or replaced entirely with a dashboard, cutting development time and cost, and lowering ongoing maintenance costs.
While there are risks associated with simultaneous implementation of NMS and OUA, there are also potential opportunities.
One of the opportunities to be had is from the increased synergies in design. Because OUA and reporting needs were considered in conjunction with NMS requirements, there is a much higher probability of system acceptance and adoption by users, truly having the system as the single source of truth, rather than depending on offline spreadsheets and other ad hoc data gathering and reporting practices that are so common. Moving to a single data repository as the single source of truth can lead to much faster and more effective decision making, and it can reduce or completely eliminate conflicting information that is common under the pressure of a storm situation. Table structures can also be designed and indexed with consideration given to the needs of OUA. This design can help streamline ETL processes, making the incremental data load time shorter.
One of the risks that can occur in a joint project is the larger number of stakeholders that need to be involved, or the added burden imposed on those already part of the effort. More tasks and a larger team increase communication and coordination efforts; if not managed effectively, these have the potential to lead to delays and/or rework, resulting in loss of time and money. More people and more use cases will also tend to make testing cycles longer, partly due to calendar coordination difficulties. When embarking on such a combined effort, it is prudent to secure early commitment from all the stakeholders.
Various studies from Nucleus Research and other analysts have shown that analytics projects typically return 10-13 times the investment. We often find that investments in analytics, when projects are properly run and accompanied by good business integration and change management, have payback periods of less than 18 months. By implementing analytics simultaneously with a source application upgrade, organizations can recoup much of the value of the investment by simply implementing it a year earlier than with a sequential project. If you have done a business case for analytics, estimate how much more you can make or save by implementing it several quarters earlier.
Many of the core functions in NMS are best monitored by well-understood processes. As such, Oracle has built many of these processes into the Oracle BI Applications. We use these as a base for implementing analytics against NMS systems for several reasons:
Oracle builds and maintains connectors to Oracle branded Utility Systems and has committed to keep these up-to-date as it evolves the underlying source application. Partners also have built their own adapters to systems Oracle does not support, like SAP, Salesforce, etc.
When you decide to upgrade a large system which has an associated analytics application, consider implementing them together. Doing so will help accelerate the returns you reap from each system, and it will reduce the time, cost, and risk of separate implementations.
Finally, as your organization implements analytics, you should lay the foundation for enterprise-wide analytics, which crosses functional, organizational, and geographic boundaries. This will enable you to address the more complex questions and problems that cross organizational boundaries and which often bedevil senior executives. Being able to answer these questions will allow the organization to thrive in challenging times.
About the Author
Karthik Mada is the VP of Delivery at HEXstream. He has over 15 years of progressive experience in BI and analytics, specifically with Oracle’s technology stack. Karthik and his team have custom-designed numerous analytics systems, including a predictive asset management system for utilities. He is currently working with several utility clients to build real-time analytics systems.