Data analytics can improve efficiency, save your organization money and resources, and fuel business growth, but it comes with big challenges. Data scientists are becoming more and more expensive, and the shortage of qualified job candidates leaves organizations scrambling for alternatives. Data silos leave some information inaccessible, and IT teams are burdened with compiling data for end users one question at a time. How can organizations combat this “supply and demand” dilemma?
The solution is simple: Enable more of your employees to become citizen data scientists. Let's break down how your organization can go about doing this, as well as why this approach is sure to improve visibility for leadership and drive more informed decision-making.
1. Create data environments with good governance
Traditionally, IT handles end-user data requests, generating a spreadsheet or compiling the data into a report. While end-users receive the answers to their initial questions, that’s all they’re going to get. If any subsequent questions arise after they analyze the data, the end-user has to return to IT with more questions and requests.
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Thanks to the evolution of analytical tools in the market, you can now empower end users to dissect the data themselves without relying on IT. But first you have to ensure good data governance so everyone is looking at the same source of truth.
Provide your end users with a raw data model – in this case, a self-service model – by pulling all your datasets together. That way you move away from any debate about who has the right information and create more consistency across the board.
2. Empower your enthusiasts
You almost certainly have employees champing at the bit to dig into data, dissect it, and share their findings. Give them the tools to turn raw data into charts and graphs to uncover insights that otherwise would have remained buried.
For example, we pull information from our service desk system to analyze the most common incident types, allowing us to spot and address recurring issues and potentially prevent them instead of simply reacting to them.
Giving users the tools to mine data can also accelerate reporting. One of our operations groups compiles senior management reports around customer operations data. This used to be an exhausting process that involved pulling, transforming, and manipulating the data into slide decks with up to 160 slides each month. It took eight to 10 people at least two full weeks to compile the deck.
However, our IT team and the operations group worked together to automate the process. IT learned all the different use cases – how the slides are prepared, what the source data is, how the data is transformed and aggregated – and created data models for each use case that take users 80 percent of the way toward their end goal.
Using the new data models, the operations team can take it the final 20 percent. The team now spends more time analyzing the data instead of collecting it, and they produce the slide decks in half the time.
[ Read also: 3 things people get wrong about analytics. ]
3. Address Excel fixation
Despite the obvious potential these new tools offer, some individuals within your organization will be reluctant to make the switch. This is especially true for those who’ve become heavily reliant on Microsoft Excel. These individuals know Excel. They’ve mastered Excel. They get the results they need from Excel. It’s going to take time and energy to learn these new tools.
It’s your job to walk these users away from their Excel fixations and toward new analytics toolsets with self-service dashboards. Individuals are always more comfortable with the familiar. You need to make this change worth their while. You need to show them how these new dashboards allow them to view and utilize data that, at one point, was difficult to get. Once the reluctant individuals recognize this, not only will they embrace the dashboards, but also can become evangelists for everyone else.
Finding your citizen data scientists
More and more companies rely on data analytics and by turning your employees into citizen data scientists, you can better mine those insights with minimal burden on your IT team’s time. While there might be some resistance from users beholden to Excel, you almost certainly have enthusiastic users ready to dive into data.
By creating a data environment with quality governance and embracing new analytics tools, you can better realize the full potential of your data.
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