Extra tags: data analytics
Authored by: CK Tan, Senior Director, Qlik
In 2021, the world we found ourselves in changed dramatically. In fact, McKinsey highlighted that the rate of new digital products and services coming to market was accelerated by seven years due to the pandemic. For the workforce, this spells even more tech and data to grapple with. Not to mention, they’re also faced with a new working environment to navigate. Gartner’s 2021 CIO Agenda: A Southeast Asia Perspective revealed that 92% of companies in ASEAN have seen an increase in business staff working from home, with 79% of companies anticipating that work from home was here to stay and might even increase going forward.
Why We Need to Be Upskilling Workforces in Data, Now
In 2022, as new variants such as Omicron cripple the reopening of countries and scuttle return to office plans globally and in the region, business leaders need to arm their employees with the skills to succeed in an increasingly digital and data-driven workplace. Upskilling employees in data is critical but it needs to be done in a more location-flexible working environment, too. 26% named Business Intelligence and Data analytics a ‘game-changer’ technology.
For businesses, training investments must go beyond just levelling-up their employees, so that they can tackle the digital and data-related tasks that already make up their day-to-day jobs. There also needs to be a focus on the future and how it will support their longer-term professional development. Why? Training is becoming the new recruitment battleground, and so leaders need to show their workforce that they are actively investing in their careers to avoid losing talent to competitors.
I’d also encourage everyone to explore more opportunities for self-directed learning, building on what started for many as a lockdown trend of learning new skills or completing on-demand courses.
There are a number of free digital resources available specifically for data literacy upskilling. For example, at Qlik we launched Data Literacy 2.0 to help drive the data fluency needed in a world experiencing continued digital acceleration. This includes over 20 online self-service data literacy classes and supporting resources for employees to upskill in their own time, split across two levels: Data Fundamentals to establish basic data skills, and Data Fluency to make confident, data-driven decisions.
Three Tips to Upskill in a Hybrid Working Environment
But, what are the best ways to train and teach hybrid workforces? Although it will vary for every business, there are a set number of principles that can be applied to most organisations:
Identify Training Needs – First, businesses need to ascertain what skillsets are needed to empower their workforce. From a data literacy perspective, this will be figuring out whether an employee is a ‘data novice’ who needs to learn the basics of data storytelling, or whether they can fast-track to analytics courses on data-informed decision-making, for example. There is a free assessment on the Data Literacy Project where employees can discover their data persona and inform their specific training requirements.
Tailor for the Hybrid Workplace – Once the training needs are confirmed, they need to be optimised for the hybrid model. For example, those with more advanced data skillsets may benefit from a mixture of in-office group sessions and one-to-one mentoring catch ups that can be conducted remotely, while data novices may need to start with onsite instruction, before progressing to self-guided training and on-the-job development. According to PwC, nearly 4 out of 5 CEOs believe that remote collaboration will last after the pandemic. The ability to access, manage and work with data is critical for all employees no matter where they are located. Implementing analytics in the cloud allows employees to access their data securely from any location and device, enabling them to collaborate seamlessly with other colleagues.
Harness the Right Tools for Delivery – Having established what is needed and how it fits with a hybrid model, businesses now need to find the tools to enable it. By combining data science and artificial intelligence, augmented analytics makes data analytics accessible for more people and enables them to get value from data by allowing them to ask questions and automatically generate insights in an easy, conversational manner through natural language processing. That might be virtual classrooms; self-directed learning through on-demand modules; or instructor-led, face-to-face training sessions – whatever it is, it will be determined by the best way to improve the necessary skillset while operating a hybrid model. AI analytics can promote data literacy by automatically surfacing insights, making recommendations, and empowering all users to confidently take action on their data. What businesses need to also be conscious of, however, is employees’ working patterns – asking someone who has already had back-to-back Zoom meetings to do a two-hour virtual classroom may not be conducive to focused, productive learning.
With the hybrid workplace becoming the norm for many in the foreseeable future, there needs to be rapid upskilling across the entire workforce for it to succeed. Being data literate can’t be a specialist skillset or limited to those with technical ability. Everyone needs to be fluent in data.
By integrating training opportunities into new operating models, and by understanding that responsibility for individual development lies with both the business and worker, companies can build capabilities, employees can improve skills and progress, and both parties can take a step towards making the post-pandemic workplace a success by driving data-informed decisions.