No data scientist? No worries. How to start thinking like a citizen data scientist
August 29, 2016
Firstly, if you’re wondering what a citizen data scientist is, it’s simply you, or me or anyone else using increasingly simple and accessible tools to understand data, rather than having to rely on, well, a scientist.
Not all of us can afford to put a data scientist on the payroll, but you can still learn how to listen to your business data.
Look for lucrative opportunities and predict outcomes
Understanding your data can help you streamline processes and identify opportunities for improving efficiency in your business, giving you a powerful decision-making tool.
Sandra Hogan, Director Business, Analytics Advisory at SAS, believes that by getting a good grasp on your data, SMEs can see where they’re losing time, whether certain areas are as productive as they could be, or if there are gaps in your product line.
You can also start to see where you should invest in your business, such as better understanding the ROI on your advertising spend, and making calls on where should be investing in when it comes to marketing.
Avoid becoming overwhelmed by the information at your disposal
When starting out, it can be challenging interpreting the statistics and data to sufficiently understand which metrics are the most important. Organising your business around one key metric is a good rule of thumb, and typically, that metric should focus on the sales side of the business.
“Explore something you intuitively know about the business,” Hogan says.
Along with analysing data in search of insight, data visualisation tools are a helpful way of presenting information to stakeholders, Hogan says. But again, focus on identifying the specific areas of business challenge, rather than the general, in order to make good decisions.
There are plenty of data visualisation tools out there that can help you, if you’re up for the learning curve. Just remember that the best tools are the ones that provide self-service analytics built into them, to assist with this learning curve.
Developing a critical eye and seeking advice
A trap for newcomers to this territory is misinterpreting the data. You want to be careful that you don’t assume the data is always 100% exactly right because most data sources are far from perfect, Hogan advises.
While analytical skills will be increasingly significant for SMEs in assessing their competitiveness, learning these skills can be a challenge, and it’s good to have resources, or a mentor, that you can turn to for support while you’re developing your data strategy.
Mentoring aspiring data scientists is something Hogan’s particularly passionate about, which is why she’s a mentor in the SAS/LifeJourney program that provides a portal for students, teachers and parents to engage in the benefits of careers aligned to education in STEM.
Consider reaching out to someone in your industry or business networks who is doing great things with data. It’s a great way to get new ideas and observe trends, as well as fostering a healthy digital culture within your company.
For SMEs looking to ramp up their skills and become their own citizen data scientist, Hogan recommends three steps.
Think carefully about your business problem in order to become confident about the data you need to look at.
Find someone already doing it or in the industry – it’s great to have a mentor who can help guide you during the early stages.
Look for tools that are easy to use to help you design and simplify your data management strategy.
What story is your data telling you about your business?
August 22, 2016
Basic reviewing of analytics and data is part of the daily workflow for most businesses. But if you can learn to read between the lines, not just see the obvious, your data can reveal some insightful stories that will help guide you.
For any business, the volume of data can be overwhelming. Retail giant Walmart, for example, really has its work cut out, with more than 240 million customers shopping online and in its physical stores. There may be a mountain of data available, but that comes with some challenges.
In order for the business to effectively sift through the multiterabytes of online and mobile shopping data across twelve websites, Walmart hired technologists around the globe to pull the best insights and improve the eCommerce customer experience.
How to manage and make sense of your data
Speaking at the National Retail Federation’s (NRF) 2016 Big Show conference, vice president of global data for @walmartlabs, Jaya Kolhatkar, highlighted four steps for making data work for you:
Data cleaning: Ensure your data is accurate and high quality, and that names, phone numbers, and emails are anonymised and encrypted where appropriate.
Hire talent: Surround yourself with data scientists, business analysts and developers with a wide range of expertise.
Make the data available: Ensure your protected and anonymised data is accessible so your team doesn’t have to be slowed down by bureaucracy.
Embrace different tech: @walmartlabs was able to build an infrastructure for the data after adopting multiple BI and analytic tools.
The results? Walmart quickly understood that customers needed an app to make the purchase process easy. The app now contains check-in, online orders and item store location features to remove any barriers to purchase.
Use data to report, analyse and forecast
You don’t have to access thousands of technologists or become a data scientist to get value out of your data.
For TrueCar, an auto price aggregation service, the small business needed a way to forecast new car sales and compile data from multiple sources. It was vital they could communicate predicative insights to investors and sell to leading automotive research sites.
The business switched to a SAS solution, Office Analytics for Midsize Business, which introduced a dashboard function displaying site metrics, marketing spend and ability to forecast car sales within 1% accuracy.
For other SMEs, forecasting and reporting might be essential for emerging trends, predicting competition, or analysing customer behaviour.
If you find yourself relying on familiar tools like spreadsheets, or are hesitant to invest in new tech, consider how data can steer you towards new opportunities by better understanding the story that it’s trying to tell.
Diving into your business data in search of pearls of wisdom seems like a daunting task until you appreciate that it’s easy to jump in without the need to write a single line of code.
Traditionally, businesses have their go-to data guy or data girl, sitting in the back office, who is called upon to do all the analytical heavy lifting, says Travis Murphy – Head of Business Intelligence Marketing with business analytics specialist SAS.
“When someone in the business needed some insight into the data they put in a request to the data guru, then the magic happened in the back office and they were simply handed back a result,” he says.
“These days there’s too much data, and also too much opportunity in that data, to leave the power of analytics locked away in the back office – we need to make it a mainstream business tool.”
One thing holding back many businesses is a fear of data among staff who are apprehensive about the complexities involved in shaping business data into knowledge and insight. To address this, Murphy often asks customers for a business spreadsheet and then loads it into visual analytics tools to show them how easily they can explore their data without writing any code.
“With our tools you don’t have to prepare your data, you just load it from a spreadsheet or even import it directly from the internet,” Murphy says.
“Seeing instant results tends to allay people’s fears and opens them up to look at their data in new ways while breaking down some of those traditional roles within the organisation.”
More than just bringing to life numbers in a spreadsheet, visualisation tools can also help find meaning in unstructured data. Text analytics goes far beyond keyword searches; it can interpret meaning and sentiment from text such as customer feedback and online comments – providing clarity and critical insights amid a sea of noise.
While it’s easy to put the power of data analytics in the hands of all staff members, it is especially empowering for subject matter experts who have a keen interest in their data, but not necessarily the analysis skills previously required to dive into that data.
“We try to cater for those people and bring them into the world of analytics as citizen data scientists – someone who uses analytics every day as part of their business but they’re not a fully fledged data scientist or a mathematician,” Murphy says.
Analytics doesn’t always look backwards, with baked-in forecasting tools making it easy to look ahead, set targets, run scenario analysis and understand the business levers required to achieve your business goals.
The exploratory nature of analytics includes support for flowchart-style “decision trees” which help align the business to reach specific outcomes. For example, the goal of raising customer conversion rates can draw on a wide range of business data to show which customer group is most likely to convert based on previous performance and the steps required to get them over the line.
“Typically, business intelligence tools act like a rear vision mirror – letting you look backwards – and it’s certainly useful to see where the potholes were,” Murphy says.
“Advanced analytics allow you to do much more, as well as looking in the mirror you can also look forward through the windscreen so you can see the potholes coming and even perform ‘what if’ analysis to steer your own course.”
Game of margins: how sporting organisations are winning with analytics
August 8, 2016
Victory on the sports field relies on a mix of brains and brawn, with successful sporting organisations making the most of their data to improve performance.
What’s this got to do with running a small business? A lot.
Data analytics is becoming a powerful tool at all levels of sport, from grassroots organisations like Football NSW through to sporting giants like the NBA’s Orlando Magic. While they play different games, the one thing they all have in common is they’ve been able to improve their revenue streams and engage with stakeholders by learning how to make the most of their business data.
Football NSW is the state’s governing body for association and indoor football, responsible for 650 community clubs. Until recently it was still dependent on spreadsheets to cope with the unwieldy amounts of data that comes with managing 227,000 players, 12,500 coaches and 4500 referees across the state.
Turning to SAS Visual Analytics to understand that data has provided Football NSW with greater insight, helping it attract and retain participants, manage referee numbers, communicate with sponsors and liaise with local, state and federal government regarding investing in sporting facilities.
Sport is more than a numbers game but gaining an in-depth understanding of members and their involvement with the football community helps the organisation better engage with them, says Football NSW chief executive officer Eddie Moore.
“Having this type of data available, and then being able to take it to our audience, whether it is a government official, sponsor or our own members, is very powerful,” Moore says.
“You don’t need to have technical skills to be able to use it – within minutes of its implementation, we were able to produce a visual representation of the analysis.”
Football NSW had been spending considerable time each month reworking spreadsheets but the larger your data gets the harder it is to see patterns and gain insight using traditional methods like spreadsheets and cross tables, says SAS Head of BI Marketing A/NZ, Travis Murphy.
“The usefulness of your data is limited unless you can put it in context and make it more personal to the stakeholders that you’re trying to communicate with,” Murphy says.
“Once they could see how every participant in New South Wales fit into the big picture, visualising on maps and drilling down with ease, they found that their data was actually a powerful business asset rather than a monthly chore.”
Meanwhile learning to listen to data has helped Orlando Magic sit among the top revenue earners in the NBA, despite being in the 20th-largest market. It accomplished this by using analytics and data management platforms to study the resale ticket market to help it optimise tickets prices and reduce churn among season ticket holders.
“In the first year, we saw ticket revenue increase around 50 percent. Over the last three years, for that period, we’ve seen it grow maybe 75 percent. It’s had a huge impact,” says Orlando Magic vice president of business strategy Anthony Perez.
Treating its data as a strategic asset and using predictive analytics allowed Orlando Magic to derive much more value from limited revenue pool, says SAS’s Travis Murphy.
“Data isn’t just numbers on a page, here it sells memberships, keeps the seats filled and makes an amazing difference to the bottom line,” says Murphy.
“Once you see the value of the analytics and senior management sees the value then it can become a strategic differentiator which drives innovation and delivers wins on and off the court.”