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BIG DATA – ANALYTICS Hiring a data dream team Analysis of data is a process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making. It sounds like such a simple thing – collect data, analyse it and draw conclusions from the analysis. Right? But where do utilities start with data analytics, what kind of information can they utilitse and what kind of insights can they be drawing from analytics? More importantly, what does a data analyst look like and where do you find them? Reports would suggest that while utilities understand in principal what benefits utility analytics can bring to their business, many are finding the implementation and planning of the analytics to be more challenging. This is due to a variety of reasons including: • No clear strategy for analytics development • Lack of internal skills • Siloed nature of utilities • Privacy and data security concerns. able to work collaboratively and independently. Analysts need to have the mindset for solving complex problems, identifying the business case, and then being able to relate the numbers and the supporting story within the organisation. Communciation skills are vitally important – while much of the analysts’ time will be spent ‘crunching numbers’, they also need to be able to explain their analysis to people who may not understand where they have drawn their conclusions from. It is important therefore to consider your data analyst as someone who combines raw talent (curiosity and creativity) with a number of skills. Perhaps the most important element of an effective data analytics programme is this – take the data and give it to the right people. A strong data base is only as good as the people analysing it. But what does it take to secure the right people for your utility analytics programme? According to Sheldon Glody, project manager at San Diego Gas and Electric, “the process of finding people with the mathematical brain power and skill sets to translate these use cases into analytics that provide significant value, is a real challenge.” A recent report indicates that utilities are looking for people that possess the ability to build models that are able to analyse the data and understand how to apply it to real business cases. Says Sabyasachi Chandra of TATA consultancy services, “the challenge for utility managers integrating data from systems that are traditionally disparaged is that it calls for staffing that can manage not only these systems, but staffing with the ability to integrate all of the data and convert that data into meaningful analysis. Utilities will typically have some skill pieces required to do this, but really do they have the entire capability?” Current estimates are that there will be a shorfall of 140 000 analytics jobs by 2018 in the US, with reports indicating that in the UK alone, the demand for data experts will be more than 69 000 by 2017. Many utilities don’t have the budgets to pay the high salaries expected from some data analysts, and yet others worry that while an expert may be good at analysing the data, if they are not seeing the business case in the analysis, the efforts will go largely to waste. E-skills UK analysed data from IT Jobs Watch to identify the top big data roles and skills and identified the top data-focused roles as business intelligence consultant, data architect, business analyst, business intelligence architect and business intelligence analyst. Process skills required for these roles included business intelligence, NoSQL, data warehouse and big data; while experience of Oracle BI EE, MongoDB, MySQL, Hadoop, Informatica and Amazon EC2 were most important. It is therefore important that utilities have a good understanding of the skills required for data analysis, preperation and management, and identify the skills gaps within the organisation. A list of development needs must be prepared, along with a list of people who could potentially benefit from upskilling or retraining. As utilities across the globe are implementing technologies which are giving them access to more and more data, utilities are having to come up with strategies and plans to manage this information and use it for improving business processes and customer experience. According to an article in the Harvard Business Review by Thomas Davenport and DJ Patil, in October 2012, data analytics could be “the sexiest job of the 21st-century.” Interesting research by Talent Analysts, a firm specialising in recruitment and analytics, indicates that the number one hiring mistake made today when recruiting analytics staff is hiring for technical skills alone. While it is essential that your analytics staff have technical skills, there is more to effective recruitment than technical skills alone. Research has indicated that hiring purely for technical skills can be limiting because it doesn’t take into consideration the other elements of a good data analyst. According to Talent Analyst, one of the most important things to consider when hiring a data analyst or putting together a data dream team is the mindset of the individuals involved. High priority qualities to look for are curiosity and creativity. Other key traits include task orientation, discipline, high level of attention to detail, process driven and 60 The Big Data and Utilities report highlights that the industry is now moving to a clearer reactive analysis (both descriptive and diagnostic) incorporating a much higher volume of historical data, with more complexity, and analyzing it much more quickly. Knowing what to look for, utilities can also yield insights from real-time information streams. Finally, with historical and real- time data at hand, utilities are also beginning to look forward with predictive and prescriptive analytics, creating real value to proactively mitigate potential operational problems before they arise.” It is estimated that utilities will spend more than $1.1 billion on analytics this year, and that spend is likely to increase four fold by the end of 2020. However, in a report by CapGemini and IDC Energy in 2013 it says, “currently, most analytics are project based. Utilities need to focus on long-term success by leveraging analytics across the operational infrastructure. They will be well served by developing a strategy that recognizes where analytics can provide the most business value and then leverage the appropriate tools and templates to recognize value.“ MI METERING INTERNATIONAL ISSUE - 4 | 2013