My experience with working around the Utility industry shows that most of the utility retailers have inherent performance issues either after they have moved to new generation billing/customer service systems or after some years of operations. They had a different experience and way of working with older mainframe based architecture.
To improve customer experience and reduce complexity in contact centres, utility retailers are moving towards system transformation. However while they thrust towards customer/employee experience uplift, performance demands increases substantially. Market competition enabled by digital channels and on-going demand from the CFO organisation to reduce IT costs, provides increasing pressure backend systems to perform well.
It is also seen some companies spend a lot of budget on initial transformation – while thinking customised solutions for unique business. The time the systems reach a point of operations, companies become extremely conscious about operational expenditures. They become very reluctant to further undergo further modernization, while many components get out-dated by 5years from Go-Live.
Then the influence of digital era, where additional analytics and self-services are introduced on the cost of the backend systems, designed a few years back. The question definitely arises “Are we really ready for it”
There are few of things utilities often miss out while in design of solutions, which becomes inherent problem in the longer run:
Right Size of the Hardware: The current SAP sizing tools does not properly size around the deregulated market and digital platform taken together. The hardware vendor provided tools are often too specific to the hardware models leading incorrect sizing.
Benchmark performance: Contact centre performance benchmarks as defined by the concerned department with the industry, are often subjective. Lack of performance level definition often misses out critical items during design.
Growth Predictions: Scalability predictions become improper due to changing energy market rules, world economy, political stability and rapidly changing technology world. Thus predictions are inaccurate in the longer period.
Retain only required data: Retailers due to sensitivity of the data and regulatory compliance often define data retention policies as “Retain all, do not archive”. This is even true of processed data carriers like IDOCS. This will lead to uncontrollable data growth.
I have experience installation with 14TB database size with only 500K customer running for 3 years.
Customer contact volumes: Changing weather pattern across the globe sometimes results in unexpected change in customer contact volume. Social media and other digital channel integration also provide some major touch points. Providing right services at the point of need become an issue.
Unique business process: Due to large volume of data and various market/customer based rule, amount of customization (esp. in SAP IS-U solution) is very heavy. This lead to performance and stability issues in the longer run.
Volume of mass data processing: With increase of smart meter data, processing more in a less timeframe become an on-going demand. Payment settlements cannot wait till end of the day, has to be posted immediate, is a typical example where its required to do more in less time.
Path towards Digitization: Multi-channel initiatives mostly work on customer, billing and consumption data. There is generally there constant data handshaking between there and backend systems. Base designs do not consider these factors.
Strategize Upgrades: When will we require an upgrade/uplift? What will the roadmap? When do we need to allocated budget? There are things which need to be defined upfront during design.
Reduce human intervention: Too many workflows lead to backlog, causing system performance issues. Later automated program act on these to close open items. Careful design needs to be executed to ensure only important items are held.
These are some unique factors customers need concentrate along implementation partners while designing solutions. This will help companies cope with backend systems with the ever changing technology, weather conditions or business opportunities.