Most utilities realize that data analytics is critical to the effective running of their organization. With the right analytics platforms in place, utilities can expect to increase sales, increase efficiency and improve operations when it comes to fraud management, customer service, risk management and strategic planning.
Despite the enormous benefits, there are still a number of obstacles standing in the way of effective data analytics:
Analytics Skills and Tools Are Lacking
There is still a major skills shortage within the data analytics sector. Utilities lack enough professionals with the skills to analyse and gather insightful information from data. Without the proper skill sets, which include critical thinking and analytical tool training, the utility’s capacity to take advantage of analytic’s potential is in jeopardy.
Since there is a lack of technically-advanced data professionals, intuitive, user-friendly, highly visual platforms are critical. However, often inadequate self-service tools and reports prevent professionals from accessing relevant data. We explore the skills issue in our article Data Analytics-The Cloud Killer App for the Smart Grid.
Lack of Training and Funds
Data is being generated at an alarming rate and is becoming increasingly complex. In order to tap in to the potential that this data offers, new tools and more critical thinking skills are required. It is therefore essential that utilities provide on-going training in this respect so that the data is used effectively. Many organisations do not always provide training for the staff in order to enhance data analyzing skills. A 2014 report compiled by Black and Veatch shows that 30.3% of their respondents agree that a lack of appropriate skills is a major challenge.
Today, more than ever before, math skills are becoming increasingly important to managers and executives. Organisations are beginning to realize that they need to increase statistics, math or quantitative skills in order to understand business processes and data better.
Organisations often blame poor data analytics on low resources. For utilities with limited budgets, efficient analytic tools that can deliver value without the high data management or administrative overhead of traditional tools are worthy of evaluation. A 2014 report from Black and Veatch indicates that 63.7% of their respondents list budget constraints as a major obstacle.
Poor Support from the Top
In some organizations, management can be wary of using analytics when it comes to resolving business problems. A lack of funding or proper understanding of data analytics can be major contributors when it comes to adopting analytics.
The Big Business and IT Departments Divide-Data is Not Integrated
In organizations where day-to-day decisions are driven by analytics, analysts need the proper tools to react to new questions and unexpected events. In order to make well-rounded decisions, analysts must have access to data from all sectors of the organization. This will make an analyst’s job easier and more valuable. Integration and consistency will also help management to make more well-informed decisions for the company.
In most organizations, business and IT departments have analytic capabilities. However, the departments often function in isolation from eachother. Because of this lack of integration, data may not flow smoothly to the business decision-makers. This can limit analytic capabilities of the organization. Often, the act of gathering all of this data can take up a lot of time. It can take up as much time as it the actual data analysis process.
There is a rising interest in analytics as both a monitoring and diagnostic tool and an adaptive planning tool to evaluate long-term plans for an organisation’s operations. It is therefore essential to overcome the various obstacles in order to benefit fully from data analytics.