This article is by Laura Petrucelli, Director of People Operations APAC at Contino, She Loves Data’s partner organisation
Changing jobs at the best of times can be challenging, let alone doing this in the middle of a global pandemic! For one reason or another, many people across the globe have found themselves in this very situation in 2020, myself included. Nothing could have prepared any of us for what has now been the single most disruptive event in our lifetime.
Resilient, progressive businesses are certainly best placed to adapt quickly and survive uncertain times like these, however, these organisations can be hard to find. I was fortunate to join a company that had already adopted all the necessary processes, technology and ways of working to transition somewhat seamlessly to remote working.
My role as the Director of People Operations at Contino is to enhance the employee experience by looking after our people, providing them with growth opportunities and strengthening our culture. Like many others, this year we were also faced with the additional challenge of helping our company navigate the new reality of remote working, all while maintaining employee engagement, productivity and protecting our culture.
My team and I came up with a number of initiatives that helped ensure a smooth transition to remote working for Contino, while maintaining normalcy in interactions with our people. In this article, I’d like to share my five tips to help your culture thrive while working remotely. Any company can still apply these recommendations as we adapt to a new way of working.
- Make remote onboarding a success
An amazing employee experience starts on day one. In a study by Brandon Hall Group, it was noted that “Organizations with a strong onboarding process improve new hire retention by 82% and productivity by over 70%.” The onboarding experience at Contino was already well structured and we wanted to provide the same streamlined experience for remote onboarding. I had been lucky enough to join Contino a week before the pandemic started having a real impact on our business, so I knew what good looked like. My team and I set out to build a remote onboarding experience which would make our new hires feel welcome and ensure they had everything they needed to be productive from day one. We sent out welcome packs, organised Zoom schedules, created welcome videos and encouraged our new starters to join the many virtual activities that Contino was organising as a way of meeting the broader team. After every new starter we would tweak and refine the process until we were happy with the program, we were fortunate enough to have ample opportunities to do this as Contino kept on hiring from a distance throughout the year.
- It starts with you, so look after your work-life balance
As leaders, we are responsible for keeping our people motivated, safe and engaged to deliver outstanding results for our customers. However, leaders are not immune to pandemic-related stress. I spend a great deal of time thinking about how I can improve my mindset so that I can adapt to new situations. As they say on aeroplanes, it is important to fix your own own oxygen mask first. If you are not in the right mindset, how can you provide support to others and do your job properly?
Work-life balance is critical, even more so now, as the lines between work and the home have blurred. My team and I regularly advise and coach our co-workers on the importance of maintaining balance so that they can be more productive in the long-term. Proactively managing the time sitting at your desk, consciously managing Zoom fatigue and ensuring your work hours do not bleed into your personal time– are all important things to consider when working remotely.
At Contino we emphasise the importance of looking after both your physical and mental health. In support of this we ran several initiatives to encourage our people to stay physically and mentally healthy and active in the remote work setting. We offered our people subscriptions to mindfulness and meditation apps, promoted mental health awareness through “Tune in Tuesdays” and “Feel Good Fridays” and encouraged the practice of gratitude by sharing positive stories.
- Ensure your people have the right remote working set up
One of our concerns as we began transitioning to a 100% remote workplace was that some of our team members would not have a suitable workstation set up to work from home comfortably. As a result, Contino rolled out an initiative called the Conti-Shop where employees could purchase essential office supplies and furniture to ensure a comfortable and ergonomic working environment. Conti-shop was a roaring success, and has been rolled out across all of our offices globally. Not only did our team love this initiative, it also helped ensure we maintained a safe working environment for our teams.
- Keep your culture alive by bringing everyone together (virtually)
Employee engagement is more of a focus than ever, to maintain productivity and keep your culture thriving. My team and I are lucky that Contino is such an open and fun place to work, allowing us to experiment with various, creative employee initiatives. At the beginning of the pandemic we launched Contini-lympics which was a fitness challenge spanning several weeks. It brought everyone together (while apart) and helped to improve the team’s overall health and wellbeing.
We also ran “Trivia Fridays”, “Dress up Wednesdays”,a cocktail masterclass and we even hired some well known comedians for a lunchtime comedy show. Occasionally, we organised dinners and lunches that were sponsored by Contino and we even sent goodie boxes to all employees to show them appreciation and love.
Contino is also very active on the tech community scene, and a proud partner of She Loves Data! We have made it a priority to keep up with our commitments, running and participating in various virtual meetups throughout 2020. We encourage our people to keep participating in these community events and to continue sharing their expertise in those forums.
- Keep in touch with people individually
Group activities are great but you should not abandon one-on-one conversations with your team and the rest of the business. My team and I made sure that we were getting in touch with every individual within the business to check how they were going during lockdown, and to offer any support if needed. I really enjoyed these conversations as they were not necessarily about work; rather it was about building a genuine connection with my coworkers even though we could not see each other physically on a daily basis.
Future: All in it together
No one knows what the future will be like. However, 2020 has shown us that we can survive and thrive even in the most unusual and uncertain circumstances. In my experience at Contino, I’ve seen us band together better and we’ve learned more about each other and each other’s families than ever before. I’d like to think that this experience has brought us closer as a company and has allowed us to form stronger friendships. I feel confident that we now have the tools and structures in place to face whatever challenges the future may hold.
This article by Katinka Gereb first appeared on the website of She Loves Data’s partner, Contino:
Over the last few decades, businesses have collected plenty of valuable customer data. However, the full potential of these datasets is not always realised.
When the data is stored on-premise, in siloed systems and without offering a single source of truth, it can be cumbersome and time-consuming to locate and validate the latest datasets, resulting in questionable reporting accuracy.
At the dawn of a new competitive era built upon an open data economy–with open banking and open energy gaining traction and telecommunications soon to follow–it is more critical than ever for organisations to understand and anticipate consumer behaviour using the power of predictive analytics, and to use these to create personalised solutions.
Needless to say, understanding your customers’ needs results in a vastly superior customer experience which boosts customer retention and ultimately generates business value.
However, before organisations can begin to turn the insights from their customer data into real business value, they first need greater agility when it comes to accessing and analysing customer data.
This means moving away from disparate and departmental reporting in favour of interactive dashboards to collect, analyse and visualise insights and a single-view customer representation to quickly interpret a customer’s history i.e. past complaints, transaction records, churn risk history, etc.. All of which enables customers’ needs to be met proactively and quickly.
In this blog, we’ll share practical steps to unlock the value in your data, including the different techniques for analysing and consuming your data as well as their benefits.
What Data Do You Need to Get Started?
The first thing you’ll need is (drumroll please…): Data.
A lack of data is rarely a problem these days. The challenge is more around how to tap into the potential of unused data, and ensuring that data quality meets the reporting standards.
Examples of possible data sources are summarized in Fig. 1 below. However, the availability of these datasets will depend on the industry, the business needs and the intended use of your customer insights.
Is the main goal to increase customer retention? Is it to tailor solutions to individual, personal needs? Is it to increase customer satisfaction by providing better customer experience?
The goal has to come from the business based on pre-defined strategy. Once the vision is clearly outlined, data scientists and analysts can help figure out the best ways to utilise the available datasets to achieve the desired outcome.
Fig. 1 – Possible datasets for customer insights
Where Do You Get Your Data From?
Examples of possible data sources
- e.g. Membership ID, industry, business location, etc.
- Useful for:personalisation strategies and painting a detailed picture of customer demographics. It’s important to note that you must follow regulatory requirements and make sure that access to PII is restricted, as dealing with sensitive, personal data raises ethical questions and has legal consequences if misused.
- e.g. How often customers make purchases, their preferred products, the value of their purchases, how long ago they made their last purchase.
- Useful for:providing information about the spending habits of customers and is useful for predicting future behaviour and analysing past habits.
- Determines how valuable a product/customer is and gives insights on what products/services customers are purchasing.
- Useful for: informing marketing strategy, and providing a better understanding of customer preferences.
- Measures a customer’s reliability of meeting their payment obligations, measuring their credit worthiness. Is the customer hitting credit limits?
- Useful for:making critical financial decisions, such as who should receive a loan, and can also help to uncover customer fraud.
- Either raw text of interactions (service requests, reviews) and/or a label/category of the interaction.
- Useful for: performing sentiment analysis and for real-time analysis of raised issues in order to inform the business on how to best address customer needs.
- To understand preference towards a certain online feature/product and measure the engagement level of customers.
- Useful for:testing marketing campaigns, choosing the right products and ads.
- e.g. Is the customer engaging with discounted offers/collecting rewards?
- Useful for:narrowing down customer segments where certain marketing strategies are effective. Additionally, engagement level is usually a good indicator of customer loyalty, i.e., the more engaged customers are, the stickier they become.
You could also utilise external data sources, such as:
- Government data: can be incorporated where appropriate. This can give a view on the socio-economic status of customers or regions, general demographics, e.g. Census.
- Competitor data: can be used to better identify when customers are leaving to obtain superior counter-offers.
- Ad-hoc datasets: e.g. bushfire relief, information on Covid-19 (stage 1, stage 2, lockdown); number of cases can be overlaid to understand the effect of the pandemic on churn rates, contact tracing etc.
How to Analyse Your Data
The next step is to bring these disparate data sources together by combining them through ETL (extract, transform, load) pipelines. By automating this step, you can make sure that the required quality controls are in place when it comes to cleaning and aggregating the data, before it can be made available for analytics purposes.
When it comes to actually analysing your data, there are many techniques to consider. I’ve outlined four of the most popular analytics techniques below.
4 Useful Analytics Techniques
1. Customer/Product segmentation using clustering techniques
The aim of clustering is to divide customers into groups that reflect similarities. The advantage compared to traditional segmentation techniques is that clustering algorithms can be applied to large volumes of data consisting of several variables (age, demography, subscription plan, transaction frequency etc.). They are also simple to train and even work on unlabelled datasets.
Popular techniques include K-means clustering, hierarchical clustering, DBSCAN, etc., and other tools such as t-SNE can be used for a 2D or 3D representation for visual consumption.
The value of segmentation is realised by the identification of the most valuable customer/product groups, allowing the business to pinpoint growth opportunities and resulting in better targeted sales and marketing operations. Understanding how different customers behave and what their spending habits and product preferences are can be easily translated into up-selling and cross-selling opportunities.
- A bank can categorise their customers based on life stage (just graduated, living in the suburbs and ready to build a family, etc.) and corresponding financial stability, analyse what demographics they belong to and develop products suitable for certain age groups etc.
- A retail provider can segment customers based on their spending habits to understand who the regular/infrequent customers are, as well as their digital behaviour and their preferred channel of interaction.
2. Churn risk modelling using predictive analytics
Customer churn refers to customers quitting or cancelling a service. Supervised machine learning techniques using algorithms such as logistic regression, XGBoost, etc., can be used to predict the churn category or churn probability for customers based on input data. This way, customers can be divided into low/medium/high churn risk buckets and treated accordingly. Low risk customers are the most loyal ones, whereas medium-to-high risk customers require more attention.
Identifying high churn risk customers allows businesses to be proactive in their retention efforts, creating on-going value through the customers who would have left without intervention. It also leads to substantial cost-savings by creating visibility into where marketing operations should be targeted, for example which customers need immediate attention and which ones deserve praise for their loyalty.
- A utility provider can build a churn prediction model based on the energy consumption history of a customer, the type of property they have, type of customer (industrial vs. private), etc.
- For irregular customers in the retail sector, time since last purchase is usually the lead indicator for churn.
3. Sentiment analysis
Natural language processing techniques, such as sentiment analysis, can be used to interpret customer feedback, and more importantly, the sentiment behind it.
Sentiment analysis is a natural language processing technique for categorising text data based on sentiment, i.e., positive/negative/neutral. Tools such as AWS Comprehend make it easy for developers to implement this technique for customer surveys, reviews, social media comments, etc.
This technique can be applied to text data of various origins (chatbots, emails, social media, etc.) to understand general feedback toward a product or service. It is particularly powerful when applied in a real-time fashion (analysing an incoming call) but it can be just as useful when used for building out the timeline of customer sentiment history–understanding if customers change their perception and sentiment over time.
- When it comes to open banking and open energy, sentiment analysis can be applied to understand what products and offers customers consider attractive, and what the deal breakers are. The open economy opens up opportunities for creating innovative solutions by combining services, providers, and offering competitive deals to satisfy demand. Sentiment analysis and other natural language processing techniques applied to customer feedback data will be valuable assets in understanding customer adoption of these new ideas and digital experiences.
4. Cohort analysis
This technique is effective for tracking how customers that were acquired at the same time (cohorts) change their behaviour over time. For example, how do the churn rates of January vs. July cohorts change over the period of one year? Is one cohort stickier than the other?
Cohort analysis relies on calculating representation (number or percentage of customers) as a function of time, relative to the starting cohort. Heat maps are a great way to visualise this change and highlight rapidly evolving groups.
This technique is useful for comparing the success of marketing campaigns, different sales and communication channels, and can even be applied to simpler metrics (e.g. demographics), such as tracking engagement over time in different states of the country.
- Utility providers can apply cohort analysis to compare the effects certain events have on different energy plans.
- A retailer can measure to what extent different marketing campaigns lead to customer conversion.
So which technique should you use?
These are just a few of the more popular techniques but, of course, this is not an exhaustive list by any means. Implementing one or two methods that are relevant for a certain use case can already make a difference in producing valuable insights and driving cost savings, but they become even more powerful when the outcomes are combined.
For example, you can look at the churn rate across various customer segments to understand if certain customer traits can be interpreted as lead indicators of churn. Is negative sentiment a good predictor for churn?
Finally, it is also important to have a centralised location for collecting and viewing this information for quick accessibility.
How to Consume Your Insights
What do you do with your data once you’ve analysed it?
Interactive dashboards, (Power BI, AWS Quicksight, plotly dash, etc.) are very efficient in displaying data in the form of charts, tables, and can be used for reporting on general KPI-s.
The Advantages of Interactive Dashboards:
Dashboards can serve as a single source of truth, making it easier to retrieve metrics, without the need to browse through spreadsheets and perform calculations every time a question arises.
- For example: With a dashboard solution, the following metrics can be easily monitored and retrieved in real time: How many customers are in a certain group? What is the monetary value associated with these customers? What is the yearly retention rate? How do the metrics perform over time? Is the business losing customers?
Besides simple metrics and global indicators of business performance, dashboards can be used to drill down and view customer insights on an individual level. Visualising the timeline of past interactions, credit or payment history, churn risk evolution etc. creates a single view of the customer and provides clarity when trying to understand present behaviour. You can get a view into how the customer is performing compared to similar segments or to the overall customer pool. Such dashboards deliver the most value when created with having the user’s specific needs in mind.
- For example: Marketing can use a customer dashboard to manage and track different campaigns, compare the performance of test and control groups over certain periods of time. A dashboard in this case would need to incorporate features that help understand customers on a more intimate level, and know how to tailor solutions to their needs.
Relevant data can be retrieved in near real-time, allowing for strategic intelligence/decision making.
- For example: Real-time anomaly detection, such as detecting outages based on IoT devices and data streams. Once an anomaly is confirmed, customers can be informed and reassured in a proactive manner.
The Benefits: Turn Your Customer Insights Into Business Value
There are a number of ways that customer insights, through dashboard solutions, can drive value for your organisation. These were touched upon already and are summarised here.
Enable real-time customer insights to frontline staff
Drive engaging and personalised customer experiences with every interaction. Through real-time visibility into customer insights such as previous sentiment, churn risk, product preferences and transaction history, customer service operations can make more informed decisions when interacting with customers increasing customer satisfaction.
Energy Central reports that a significant number, 72% of customers expect customer service representatives (CSR) to be informed on their product and service history when they contact the provider. Under such circumstances, CSR-s only have a few seconds to solve a customer’s issue.
Increase customer growth opportunities
Increase customer growth opportunities by understanding customer needs and creating highly personalised solutions to satisfy individual customer needs. Understanding customer sentiment towards a product or service, supporting customers by quick issue resolution and identifying the next best action thanks to real-time analytics.
In a recent survey, EY outlined how during the accelerated digital transformation induced by the COVID-19 pandemic, personalised solutions that are able to satisfy customer needs can be a real differentiator for financial institutions. Real-time, data-driven insights, underpinned by solid architectural design allow businesses to continually adapt and evolve, and respond to customer needs.
Protect existing revenue and increase customer lifetime value (CLV)
Put preventive churn measures into place and proactively engage “at risk” customers. Customer acquisition is pointless without customer commitment and long-term lifetime value.
In the Qualtrics Banking Report, 550 banking customers were interviewed, where 56% reported their banks made no effort to keep them when they announced they were churning.
Decrease acquisition costs
Lower costs by creating more personalised solutions, instead of targeting the entire customer base with campaigns that do not apply to certain audiences. Understand customers on an individual level, and offer the right solutions.
McKinsey talks about personalisation in the context of disruption, and points out how retailers can use personalized marketing to drive growth and reduce acquisition cost. “Leading retailers create a 360-degree view of their customers—where they shop (online or in-store), what they shop for, when they shop, how much they spend, what they view or click on—and target them with highly personalized offers based on that data. These retailers use personalization engines powered by machine learning to improve e-commerce websites and their marketing campaigns across channels. “
As a final remark it is important to note, if the data maturity of the business is low and analytic solutions are new to the business, upskilling employees will likely be a necessary step in the adoption process. In alignment with the strategy and vision of the company, dashboards and analytic solutions should be introduced to solve business problems. Without this alignment, the adoption of ML solutions will be limited and untrusted.
Are you ready to transform your business and turn your data into insights?
Get in touch!
Share a little about yourself.
When I was younger, my curiosity in unpicking the invisible forces that shape the world drew me to study International Relations. It was the same curiosity that later led me into data journalism and data science. Today, I’m a self/community-taught programmer and data viz geek working as a data scientist at Synthesis, a specialist in growing audiences and changing preferences.
What was your job like before transitioning into data science? What prompted you to make the transition?
I started out with the Maritime and Port Authority of Singapore, working on international maritime affairs. This gave me an inside view of diplomacy and policy-making in a global industry. Later, as part of the strategic planning team, I researched key trends and developments that affect Singapore’s future as a maritime city.
I didn’t realise it then, but discovering journalist sites like Fivethirtyeight and the Pudding was the beginning of my career pivot. It blew my mind how they combined code, data, design, and story to uncover and bring to life the larger patterns in socio-economic, cultural, and political issues. I was fascinated and wanted to learn how I could do something similar.
What is your job like now? How different or similar is it to your previous role?
I create custom datasets and use tools from network science and natural language processing to help build a picture of people’s preferences and behaviour.
It was a huge transition in several ways: I moved from a government agency to a fast-growing company with a startup feel; from an industry with centuries of history to a new world of open data and marketing insights; from a policy role to a data science and engineering role. However, it really wasn’t a sudden switch.
So how did you go about making the transition?
Whatever I was learning on the side—computer science, Python/R, new data visualization techniques and statistical analysis—I tried to apply it in my job or personal projects. I also got more involved with communities like She Loves Data, Singapore’s Hacks/Hackers meetup group, and the Data Visualization Society.
Then came a point where I felt a need to add more structure to my learning. I took a sabbatical and went for the Metis Data Science bootcamp, with support from IMDA’s Tech Immersion and Placement Programme.
But how I found my current role was rather fortuitous. I first got to know the people behind Synthesis when I joined a data storytelling challenge that they co-organised. My entry, which re-imagined and visualized popular wedding songs as cupcakes, made an impression and I won a commendation. Shortly after, they were expanding their data science team, and one thing led to another.
What were the major challenges?
Learning to silence my inner critic when it’s not being helpful. In my first two weeks, I came close to a burnout because I thought I needed to grind it out in a new work environment when I didn’t have to. It was tough but I had to learn how to be kinder and more patient with myself.
The fact is, when switching careers, it’s easy to feel overwhelmed and it’s OK. You’ve got to accept that it will take you longer to understand and figure out things that may be second-nature to more seasoned professionals.
Were there any pleasant surprises? Maybe you were shocked at how easy some things could be?
In a way, simply pursuing my interests and skilling up led to open doors. I didn’t have to search hard to land my current role. Even before entering the data science field, there were always ways to practise aspects of it in my day job as long as I kept an open mind.
In my new role, I’m fortunate that my more experienced colleagues are super supportive when I reach out for guidance or simply to bounce some ideas off them. Even though my background is non-traditional, I feel very much part of the team.
If you were to go back in time, what advice would you give yourself on this journey?
Making the switch is only the beginning. I don’t think we talk enough about what comes after the switch as well as the non-technical skills needed for a happy, healthy work life in the data/tech industry. Aspects like self-advocacy and self-care are important too.
Has volunteering at SLD helped you in your transition journey?
As a blog editor with SLD, I came to know and interviewed many accomplished brave women. Their own career transition stories inspired me and I learned from their wisdom, hindsight, and experience.
Being part of SLD also means being surrounded by other women and male allies with a can-do attitude who cheer each other on. It’s so uplifting!
Anything tips or advice you wish to tell all our readers? 3 tips you would like to share with our readers who are considering switching roles & industry?
- Don’t worry if you don’t have a passion to pursue. Instead, stay curious and focus on mastering skills. I didn’t start out with a fixed idea of what I wanted to do or have some burning passion to begin with. That used to trouble me, but eventually I learned it didn’t matter all that much.I would recommend reading Cal Newport’s books So Good They Can’t Ignore You and Deep Work. He makes a compelling case that it’s ultimately people’s skill-set and not necessarily their passion that determines their career path.
- Beyond skills, things not obviously connected to work like your social habits and lifestyle choices will shape your career transition. Guard against toil glamour and burnout. The You Got This network is a great resource.
- And remember, your job is not your career. In the words of Earl Nightingale: Jobs are owned by the company, you own your career!
Sep 07 2020 | Nikita Phavade
Meet Loucine Hayes, the head of our new chapter in Armenia! With decades of experience in international development and capacity building, Loucine has touched many lives. We’re delighted to have her as part of the She Loves Data community, and here, she shares her story as well as vision for the new chapter.
Share something about you.
I repatriated to Armenia last year after living in 14 countries and working in over 27 counties in various fields. But I’m always focusing on building communities, effective business models and functioning policies. Throughout my career, data has been the pulling thread to stitch all pieces and decisions and make a wonderful tapestry. And now I am in Armenia to share all wealth, do knowledge and experience, inspire and guide young people to make bold steps toward attaining their dreams.
How will the launch of this chapter be a milestone for Armenia?
Armenia has made strides in IT and Data science. Sometimes it has been called the new Silicon Valley. There are many wonderful opportunists for women to get engaged in this industry and make better career choices, better solutions for their endeavors in entrepreneurship and other fields. Data can guide and help them thrive. The trend is there for women to get engaged and this will open a wide gate of opportunity and inspiration not to be afraid and make a bold step. The American University of Armenia Open Education (AUA OE) has a strategic focus to increase the engagement of women in the regions. We have the infrastructure and She Loves Data has the outlet to the world of knowledge in this field and together we can bring invaluable opportunities for learning and growth in this field for women.
How can members join your chapter? How will it help them?
Members can join by filling the volunteer form on She Loves Data website or sending a letter of intent. We will also have special events and meetings to explain and encourage members to join.
It will help them to get up to date training and skills in the field as well as make career advancement or start a career in this field. It will help them to network and meet other members and exchange of experiences and support.
What three things you would like to say to the young women in Armenia?
- Be unapologetically bold when pursuing your dreams.
- Be gentle and compassionate when dealing with others.
- Embrace fun and joy in your life with every moment and every step.
What is your vision for the Armenia chapter?
Opportunity for every woman to attain a meaningful career in a data-driven world.
Share with us events or topics that the Armenia chapter will be promoting.
Career opportunities in data and connection to various industry leaders. Sub-sectors can be banking, health, education, agriculture, circular economies and environment protection.
Coding and algorithms.
Interview with Jana Marle-Zizkova, Co-Founder and Managing Director of She Loves Data and Leanne Robers, Co-Founder, She Loves Tech
Leanne Robers, Managing Director, She Loves Tech
Q1. Share with us your first meeting with Jana.
I met Jana in 2019 when she applied for the She Loves Tech competition under her start-up company, Meiro. We organised an event for all finalists in Singapore that was sponsored by Zalora. Jana and I immediately connected and knew that this friendship would continue even after the event. We had drinks a few weeks after and spent hours talking about all the potential opportunities for collaboration between She Loves Tech and She Loves Data and realised that we have so many things in common. Jana is passionate about growing the women in the tech community, a highly inspiring individual and such a powerful force to reckon with!
Q2. Why are organisations like She Loves Data and She Loves Tech, is important for women and tech?
Both organizations create opportunities for women in the tech space. She Loves Tech’s grand vision is to encourage more women to step up in technology businesses. Whilst, She Loves Data’s mission is to inspire more women to pursue careers in Data and Tech. In my view, one of the approaches to drive this common goal is through collaboration with key partners like She Loves Data, that is to empower women in technology. Jana has empowered so many women over the years and I have heard stories from volunteers who have grown passionate about data just being part of the movement.
Q3. Share with us some of the plans for the collaboration?
We are still very much at the early stages of our discussion in terms of supporting each other and working through our collaborative plans. We have been invited to speak at Asian Professional Speakers Convention on 31st August, 2020 and it’s our first event together representing She Loves Data and She Loves Tech. This is just a start, to many more things to come.
Q4. Your advice to women who are considering starting their own start-ups?
I have a bookful of advice as I have learned so many things over the years by making so many mistakes in developing technology start-ups and here are a few thoughts: –
- Be bold and be brave, never be afraid to ask for help.
- Technology is a means to an end. When building technology, ensure you are building a solution to solve an important problem. Allow the technology to follow the problem and not the other way around.
- When experimenting with technology, it’s all about timing, in launching the product. Sometimes the product works and sometimes it does not work due to market forces. Thus, always be kind to yourself and keep trying till you succeed.
- It is critical to have a strong team who complement each other’s strengths and are aligned with a common vision, goals and values to contribute to the overall success of a start-up.
Q5. Final words to our readers …
Do follow us on social media as we organise competitions in various locations and the women founders would benefit from participating in these events and learn from each other and the supporting partners as well.
Jana Marle-Zizkova, Co – Founder and Managing Director of She Loves Data
Q1. Could you share with us, how did this partnership come about?
I was pitching for my own start up last year with She Loves Tech and I was very impressed with the level of professionalism for the pitching competition, the level of support for female founders and the clear feel of the community’s presence. She Loves Tech has a foot print in more than 30 countries and I thought it would be great to collaborate. Leanne Robers, the Managing Director, of She Loves Tech and I met to explore collaboration between both organizations and both of us felt there were mutual benefits for us to come together and support the wider community, to reach out to more females.
Q2. When are you planning to announce the collaboration?
We are announcing the collaboration as we speak.
Q3. Share with us some of the upcoming plans?
- We want to talk about She Loves Tech’s pitching competition amongst our community to raise the awareness of the event in all respective countries.
- There is an upcoming Conference by She Loves Tech female founders and She Loves Data is planning to participate and offer data literacy sessions for the founders.
- For the She Loves Data community, we will have the opportunity to introduce our community’s educational programs in places where we are currently not present and invite those who might be inspired to start chapters in their home locations.
Q4. Tell us why you are excited about this collaboration?
I met other women founders and Venture Capitalists as part of my interactions with the She Loves Tech community. I met some of the female founders and was so inspired by them and I personally felt that being part of the competition was a once in a lifetime opportunity. I am super excited about supporting women entrepreneurs out there. I believe in collaboration between communities, instead of viewing the groups as separate entities. I hope this is just the beginning. We will find more ways to collaborate and support She Loves Tech. Leanne and I are very passionate and committed, and we will do our best to create and build a meaningful, long lasting partnership.
If you are a female founder, apply here: https://www.shelovestech.org/2020-key-dates
Please share a little about yourself!
I am the founder of my online business “The Secret Pet Store” and a part-time social media specialist for She Loves Data (SLD). I was always passionate and excited to run my own online business. So, when my Reporting Analyst role got impacted due to covid-19 I thought that this is the best time to do what you love to do… I joined SLD to serve the community and also launched my online store.
What was your job like before transitioning into your independent firm? What prompted you to make the transition?
I always knew in my heart that I wanted to start my own business and be a renowned best social media strategist. I never saw myself working until the age of 65 and that too in a field which I am not passionate about. Plus I always wanted to do something for our loving pets <3.
Also, we all know it’s not easy to simply leave a good full-time job and start again from ground level. So I think it was meant to happen, as my role got impacted by COVID and I started my dream journey. However, I also began my travel page on IG while I was working.
What is your job like now? How different or similar is it to your previous role?
Its a lot of hard work now definitely much more than before. There are lots of uncertainty and risks however the main driving force is that I enjoy & love to do this.
I would say this is completely different from what I did before, as I am coming from a data analyst background into social media marketing 🙂 also 100% more exciting then analyst role! Hahaha
So how did you go about making the transition?
It was really tough as I changed my field, I knew I had to start from ground zero. I had to do many online courses and thanks to my friends who helped to keep me motivated on the days I was about to break-down and when I started doubting myself. Being an experienced analyst, it was a bit easy to get a similar, well-paying role but changing to a new career required me to start from entry-level roles or maybe internship
What were the major challenges you faced?
- Not enough work experience
- Time management
Were there any pleasant surprises? Maybe you were shocked at how easy some things could be?
Yes definitely. I was at the first scared and overwhelmed with social media tasks at SLD as I knew it would be read globally, but now its fun and I enjoy it. For my online store, building the whole website from scratch was one of the things that I first felt would be so tough but turned out to be easy.
If you were to go back in time, what advice would you give yourself on this journey?
I should have believed in me and should have started working towards my passion sooner. But then I am happy as its never too late!
How has volunteering at She Loves Data helped you in your transition journey?
Absolutely! SLD gave me a chance to further develop and improve my social media skills. It gave me a platform where my knowledge and learnings can be implemented.
Bonus: I gained a lot more confidence as a social media specialist 🙂
Any tips or advice you wish to share with our readers?
- Be prepared to work harder than before
- Have a schedule & try to gain as much knowledge as possible
- Don’t be afraid to follow your dreams!
Our Origin Story
It all started with a simple question: Where were the women? When Jana Marlé-Zizková and Pavel Bulowski went to work meetings or events in the tech industry, the other attendees were often men. They discovered that many women had a lot of enthusiasm and interest in data analytics and related areas. Yet, not everyone knew how to get started or access community support. This inspired the first workshop on data analytics for women in 2016. In the face of overwhelming response, one workshop led to another, and then to many more. She Loves Data was born.
As a community, we commit to the belief that women have many talents, virtues and value to bring to the table. This bears out in our very own logo, which is based off the Coxcomb chart. Florence Nightingale famously used the chart to explain the preventable deaths of soldiers during the Crimean war. She later led the sanitation reform of British hospitals. Just as Nightingale used data to create change, so too can more women become active contributors to a data-driven world. Pam Ooms, our volunteer who designed the logo, felt that Nightingale’s story fitted very well with She Loves Data’s purpose and wanted to borrow design elements from the Coxcomb chart.
Today, 200 years from Florence Nightingale’s time, she continues to inspires as a role model. We also find ourselves in the midst of a crisis, where the need for data literacy and digital skills is more urgent. We are forced to adapt to disruptive changes and in many instances, shift from the physical to the virtual. One silver lining is that the transition has led She Loves Data to create our first webinars, and we’re able to reach more people. At the same time, our community focus remains core.
It’s important that women building skills in tech don’t feel like they are in this journey alone. We understand that it can be tricky to build this feeling of community and sense of belonging online. There is no easy solution, but we can continue to support each other with friendly exchanges in our Facebook and LinkedIn groups. She Loves Data also continues to expand. We’re building local tribes and partnerships in places from Armenia to Vietnam so that more women can benefit from our work.
We hope you keep safe and stay strong.
These are some of our most dedicated volunteers, ladies who overcame their own mountains and pay it forward by building up our #DataTribe. Say hello to Kathleen Criselle Reverente, a data scientist a Novare Technologies who heads She Loves Data’s Manila chapter.
Could you share a bit about your career journey? How did you shift from Broadcast Communications to Software Development to your current role as a Data Scientist?
After I left my media job, I began searching for a career that I wanted to pursue. I remember asking, what will align with my interest in sharing stories and insights and move people? At that time, I didn’t know the answer. I went about with the openness to learn new things and trust the process of finding my career path. I landed different roles, including as a production assistant, a training assistant, and a sales associate in different industries.
It was 2018 when I interviewed for and won a scholarship to a web development bootcamp. The scholarship sponsors had the mission of encouraging women to pursue a career in tech. At that time, I was healing from my first miscarriage and felt lost with regards to my career. But I remember my mantra at that time was to say yes to opportunities. After completing the bootcamp, I was still not yet confident in shifting career to tech. Self-doubt crept in. I got overwhelmed with the jobs available as most were looking for bachelor’s graduates in Information Technology or Computer Science. Luckily, another scholarship opportunity for a web development course came along. After that course, I got an internship as a front-end developer. A few weeks after, I found out that I was pregnant and needed to be on bed rest. That pregnancy led to another miscarriage.
During this time, December 2018, I hit rock bottom. I didn’t know what to do next. I was sure that I had wanted a job in the tech industry and I would have taken on any job. I’m grateful that at the start of 2019, the company where I had my internship, offered me a Junior Manual Quality Assurance role. I enjoyed it because I had learned so many things. I discovered I loved analyzing systems and workflows, my discussions with developers and the product team, and also anticipating possible problems with our systems. In short, I loved everything!
Around that time, I saw a Facebook post on a data science scholarship for women and applied for it. In March 2019, I heard back and was invited to do the next steps in the application. I later got the scholarship, which offered an immersive data science learning experience.
In August 2019, I needed to make a big decision on which career path to pursue: Software testing or data science? I decided to go out of my comfort zone to finally pursue a career in data science. I received feedback that I was still far from landing a data-science related job, as I needed to learn more. So I kept on learning. I got lots of rejections in job applications. I remember there was a time, I cried during an online take-home exam with my dream data science company. I had the idea on how to do the exam, but it seems that my skills weren’t enough to execute it.
Again, doubts crept in on whether data science was for me, and I set a deadline of January 2020 to land a data science job. Last February, I started at my current company and I’m so grateful that they saw the potential in me. Every day, I’m happy to learn more about data science and its opportunities. Due to my current role, I get to know more about my learning style and my love for learning. Indeed, learning never stops and I’m loving it!
What inspires you to be part of the She Loves Data community and give back?
I found out about She Loves Data (SLD) in an Instagram ad way back in 2018. At that time, I was following different women tech groups that have local chapters in Manila. When I heard that SLD was going to have their first event in Manila in September 2019, I made sure to be there! I was like a fan girl at that time! It was so exciting to experience an event that I saw about in Instagram posts and stories. That was also when I met the co-founder Jana Marle-Zizkova.
She Loves Data played a part in helping me get to where I am now. Because of the SLD event last September, it widened my perspective that I would find my place in this field and that I need to keep on learning and going. There’s a community that will always there to support someone like me.
I spent my volunteer time by connecting to other communities here in the Philippines for future collaboration. I also share the current online SLD events. What inspires me to part of She Loves Data is that it is one of the communities that I’ve known that really encourages women to pursue a career in tech. As a career-switcher, I find it important to have a community like my support group, especially when self-doubt creeps in.
Is there anything else you would like to share? Do you have any advice for community members facing self-doubt in their career choices?
With the roller coaster journey that I have been through, I find that my experience with self-doubt keeps me grounded on how badly I wanted to pursue a data science career. What works for me is to find time to confront that feeling. I write thoughts that I’m having at that time and identify what triggers that feeling. After that, I read and process whether there is something I can do about it. If possible, I list down the steps.
Whenever I’m tackling self-doubt, I always end up being reminded of my why in pursuing this career and to trust the process! It’s best if you have someone or a community who have similar goals and you can share your progress with them.
Our events and workshops wouldn’t be possible without our awesome volunteers who dedicate their time to sharing their knowledge in tech and beyond. Say hello to Dalya Manatova, volunteer instructor, and Steve Remington, our director of curriculum.
What inspires you to be part of the community and give back?
Dalya: Switching careers to Data Science/Data Analyst positions is not a path for everyone. However, shaping an individual’s career such that it intertwines with data and relies on data-driven concepts—that’s the goal. I am filled with joy when I have an opportunity to show others how they can utilize data in their career. I help people understand the material during the workshops and make sure everyone is on track.
Steve: Two things. First, I was fortunate to have great mentors both professional and academic. Given that I am good at sharing my knowledge in a way that makes it easy for others to understand, this is the best way for me to give back and help prepare the next generation of my profession to be the best that they can be. Second, I want to help redress the gender imbalance in the analytics profession and the associated negatives that it sometimes brings. Also, I have taught, worked with and managed a number of female analytics professionals in my career. I have always found them to be equally or often more capable than their male counterparts. I want to share that with other women so they can shift from the “Maybe I can’t do this” mindset to the “I can definitely do this” mindset.
These are some of our most dedicated volunteers, ladies with a knack for building up our #DataTribe. Say hello to Jitka Raskova and Richa Tibarewal, our lovely co-heads for She Loves Data’s Singapore chapter.
How do you spend your volunteer time with She Loves Data?
Jitka: At this moment, I spend most of my time planning and organizing webinars for the whole SLD community in APAC. We run approximately 2-3 webinars per week focused on 3 main areas: Data & Tech, Digital Marketing, and Essential Skills. I am happy to share that since we have implemented our online strategy in the middle of April 2020, we have welcomed audiences from more than 51 countries and we have reached more than 2,000 unique registrations.
Richa: The time that I spend working for She Loves Data community is my personal passion time. The energy rush that I get by working for the women community is fantastic. At the end of the day, it is not about what you have or even what you have accomplished. It is about whom you have lifted up and what you have given back. I build long-term relationships with the partners of She Loves Data to bring more workshops to our community. I also work with various internal teams behind the scene to make sure we are consistent, strategic and relevant in whatever we do. As we are a volunteer-run organisation, it’s important to do reality checks and see if our activities are meeting real needs. Helping volunteers use their time fruitfully is another responsibility that I love to drive.
What inspires you to be part of the community and give back?
Jitka: As a mother returning from my maternity leave, I find that She Loves Data has given me an opportunity to be part of this inspirational community. This volunteering role allows me to learn a lot about how business and event management works in Asia. I have the chance to meet and talk to people from various countries, cultures and various business sectors. I love the enthusiasm and energy you get from the community members who attend our events. It’s truly rewarding to hear that we are able to help someone to find a job or that we encourage women not to be afraid of Data anymore. I also learn a lot while actively listening to these webinars and attending events myself.
Richa: The gender gap in the tech industry is still huge. This is why we do what we do! I strongly believe, an inspiring woman is simply a woman who can fill someone with the desire or urge to do something worthwhile, leverage their talent, and explore their passion. She Loves Data enables me to do my bit towards building a community where like-minded women can come together to learn, share knowledge, support each other, connect and have fun!
There are so many women out there who genuinely wants to learn. They want to switch their careers or get back into action after taking a break. Post-workshop, we get so many encouraging emails from participants. We have seen women landing unexpected opportunities because of She Loves Data. It could be a remote work opportunity with our partners or a networking opportunity that created a path for a new job. These are the stories that keeps me motivated. The entire team at She Loves Data is self-driven, and I get to learn so much from the team!