Throughout the course of the pandemic, the concept of a ‘pivot’ has been all too familiar to businesses across all sectors. In the face of remote working practices, lockdowns, and social distancing restrictions, many organizations were forced to rethink every aspect of the way they do business – from in-house issues such as training and the minutiae of internal processes, to more radical transformations involving the business structure and product offerings themselves.
Through all of this, one thing has remained vital: data. Generally speaking, organizations must always have the necessary evidence, and indeed numbers, to provide the rationale for any major business decision or overhaul. Even outside the context of Covid-19, if businesses are to stand the test of time, they must continually innovate by adapting to new trends and catering to a changing set of demands.
To do this, it is vital to build a modern data strategy.
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Reinventing with data analytics starts at home
Firstly, businesses must look inwards to keep up with new opportunities to grow and pivot. This should start by building the right organizational culture and infrastructure required to embrace sophisticated data analytics, as well as providing staff with the knowledge they need to harness these technologies effectively.
In recent months, businesses have experienced wavering confidence in their ability to equip employees with the appropriate training and resources while working from home – according to a recent survey from Soffos, one third (33 percent) of organizations say they lack the tools and knowledge to effectively support remote staff. And employees seem to agree, with the same number (33 percent) stating that online learning solutions have been too generic to help their professional development throughout the pandemic.
This is where next-gen learning management systems (LMS) that provide actionable business insights would come in handy to push the needle forward on staff development, and in turn, create the right conditions for innovation and meaningful change. In an environment where videoconferencing sessions and breakout rooms tend to provide a ‘blanket approach’ to corporate learning, and staff are unable to learn through osmosis from their colleagues, organizations would do well to look to LMS platforms and eLearning solutions powered by the likes of artificial intelligence (AI).
As well as alerting administrators as to any glaring knowledge gaps that employees might have, training managers will be able to track individual and team progress on particular tasks, see which questions have been asked and by whom, and view knowledge silos on an individual, or a team basis. In essence, cutting-edge analytics software will be able to provide business leaders with the insights they require to personalize their training initiatives, so that their staff are ready to embrace whatever changes might come their way.
Beyond just filling knowledge gaps and ticking off compliance exercises, these additional insights and metrics should ultimately equip staff with a greater level of satisfaction in their roles. Learning analytics technology will help managers and training leaders develop programs that constantly deliver. Staff will be able to learn more quickly and effectively as a result of more targeted learning paths, and ultimately achieve better outcomes because their learning could be measured, understood and responded to.
Given that analytics will delve into the minutiae of the everyday and uncover areas of greatest need, employees will no doubt be able to go about their day safe in the knowledge that they are in the driving seat when it comes to their professional development. Advanced analytics software can collect information without the need to directly ask staff what they are struggling with, or what changes they would like to see from current training programs. Ultimately, modifications can be made without any awkward conversations.
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The power to pivot
Away from training initiatives, businesses should look to migrate their data to the cloud, unify their data by breaking down data silos, and then plan to innovate with the data gained throughout this process by using analytics, artificial intelligence (AI), and machine learning (ML) technologies to simplify the process. Migrating data over to the cloud will enable businesses to scale in a cost-effective manner as the volume of data being captured grows, allowing them to pay for only what they use, and make information readily accessible to those who require it. In doing so, businesses will have the firm foundations required to make quick and informed decisions, but also the power to do so more efficiently than ever.
Put simply, the more data organizations have to back up their choices, the better – any organizational transformation that is evidenced by a store of data will have a greater chance at success. On the other side of the coin, these initiatives will also pose less of a risk, if the changes require substantial investment. That said, there is a limit to the amount of data that any one analyst can interpret alone. That’s why looking to platforms that utilize AI and ML technologies will provide businesses with the ability to innovate using insights gleaned from copious amounts of data, that would overwhelm even the most accomplished of teams.
A subset of AI, the main objective of machine learning is to effectively process and make use of mounds of complex data that is sourced from various data points. Whether it is determining customer trends, predicting buying behavior or detecting fraud, AI-powered solutions empower businesses to spot and maximize opportunities, and ultimately make the most of developments that would otherwise be out of reach.
Resulting business decisions can be as small as implementing a new training scheme to re-skill staff in line with new company developments, or as large as providing the impetus for major investment decisions, based on a wealth of data. The key is that algorithms will be doing all of the hard work.
Ultimately, the pandemic has been a great reminder of the power that data holds when it comes to the enduring need for businesses to reinvent themselves. Given that some 52 percent of businesses surveyed by Soffos.ai plan to up their investment in this area in the next twelve months, I will be watching on in anticipation to see how organizations across all industries step up to the task.
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Nikolas Kairinos , chief executive officer and founder, Soffos