But at some point, he says, the organisation begins to outgrow the tool.
“They need help as more and more data [arise] from various systems that they use, and they want to integrate those systems so they can use all of it and try to make better decisions.”
“It is quite difficult if your only tool kit is the spreadsheet.”
Felton says this was the situation MainPower found itself in when it assessed the information held in its different systems.
MainPower has been distributing electricity to homes and businesses across the North Canterbury region for nearly 100 years. It services over 37,000 customers via 4,873 kilometres of overhead lines and underground cables across an area of almost 12,000 square kilometres.
It keeps data not only from its operations and customer records, but also flora and fauna around New Zealand.Read more: How CIOs can shift to a 'digital first' ERP mindset
Identify first of all the different data systems that are important to the organisation.
The latter information is critical as trees are often responsible for power outages when they fall on electric lines during storms.
Most information is sourced through a GIS system to map all assets with coordinates. The organisation also uses Tech One for its ERP.
“They were looking for something better, more nimble than the spreadsheet approach they were using,” says Felton.
“They wanted to find a tool that can help bridge the cultural language, the way of thinking, between the engineers who are very technical in their orientation and all of the staff with different backgrounds.”Read more: Multi-speed IT needs multi-speed CIOs
In a report prepared on the BI deployment, Sean Fahey, database administrator at MainPower, describes the situation then: “We were experiencing an influx of data from each source. Our analysis method simply couldn’t keep up.”
The data was ‘siloed’, located in sets that did not ‘speak’ to each other, notes Stuart Wilson, network manager of development, MainPower.
Our analysis method simply couldn’t keep up.
“We wanted to reduce conflicts within the organisation because at that stage we had everyone looking at data sets from different perspectives; there was no unity of information, methodology or centralised depository.”Read more: 10 things CIOs need to know about agile development
“We also feared that important connections between sets were being overlooked. We simply had no way of compiling and easily viewing data sets collected across different departments and maintenance history,” notes Wilson.
Felton says Fahey and Wilson, coming from broad areas of the organisation, formed the core team that was proactive in utilising the data.
They had the support of the CFO. “They were pivotal in moving the project forward,” says Felton, who was tapped to help the organisation implement a business analytics system to go across these data sets.
Felton says a key advantage of MainPower was it has already done preparatory work. The company started to build a data warehouse to make the data held in multiple systems centralised, useful and accessible.Read more: Tour de France provides platform for big data analytics
“In general, once we started to work with them and did a proof of concept there was just a lot of support for the organisation for going forward,” says Felton.
Working with Montage, the company looked into six BI systems and chose Tableau.
Felton explains Tableau has very good mapping capabilities. “Its visual approach to data analysis means everybody can relate to the content very quickly.”
These were easy to use even for those who do not have GIS software training, says Felton.Read more: A third of SMBS have never used cloud computing: The Alternative Board
Using the software, he says MainPower created maps that visualised all the hardware that constitutes the electricity grid they manage. They then tagged Tableau when these are due for inspection and maintenance.
Information was displayed on a geographical map, allowing MainPower to reorganise and optimise its maintenance schedules.
“They optimised a lot of their maintenance work because of that,” says Felton.
He says this was not possible in the past because the data will be in different data systems.
So what key advice can he give to companies that are looking at a similar BI deployment?
We wanted to reduce conflicts within the organisation because at that stage we had everyone looking at data sets from different perspectives.
“Develop your business intelligence capacity incrementally,” says Felton.
“Identify first of all the different data systems that are important to the organisation.”
“Look at the different data sources you have, and then talk to all the chief stakeholders what are the major drivers of the business,” says Felton.
“What are the question they really need and want to use the data to help answer? Then we help them come up with a list of potential projects to get started with BI.”
“Arrange those in a way that what you want to do is initially pick the ones that have the most business value but at the same time have relative low scope so they can be accomplished very quickly.”
“If you are able to start with that, you are able to show the business very quickly the business benefit of investing in the BI work,” says Felton.
Felton, whose previous roles included deputy commissioner and CIO at the New York State of Mental Health, says this incremental approach has worked in a number of BI deployments he has been involved in.
He concludes MainPower has two advantages. First, it had a cross disciplinary group that was already working together and “committed to finding a solution”.
As well, “They have done a fair amount of preparatory work at the database level already so that made it easier to capitalise on the data they had.”
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