Businesses are always seeking improvements in how they process and analyse large volumes of data. The usual business case is that it’s a major boost to efficiency and effectiveness – but there’s more human factors too. A data-led approach brings benefits to customer satisfaction, product and services, and employee engagement – when done effectively.
Research by Harvard Business Review (HBR) and ThoughtSpot showed that 41% of businesses expect frontline workers to be using AI in the next two years. So if employees are resistant to transitioning to new practices, there needs to be a look at the corporate culture. This goes beyond just a reluctance where people have not used data-centric processes before. If a culture isn’t setting standards for openness, critical thinking, and innovation, it cannot be a high performer or a leader in its space, long-term. That HBR research found that executives at companies lagging in achievement are ten times more likely to say their teams shouldn’t be able to make decisions using data.
This is problematic because no matter how differentiated the solution, impactful the use-case, or strong the executive support is, if no one uses data and smart technologies then immediately useful benefits are lost.
As a result, to generate business value through new technologies, organisations must create a culture and environment that encourages user adoption of critical thinking and reliance on the right data at the right time to make decisions. To do this, meaningful change needs to be applied to how companies work to empower their employees to have the confidence and desire to make data-backed decisions. Thought this, employees will provide demonstrable value through data-driven insights and vitalise their own skill sets and careers. Building this data culture starts with providing straightforward access to the data employees need using their own business language and context via accessible technology. It’s worth it. HBR found that 72% of organisations empowering those on the frontlines with access to data are seeing gains in productivity, 69% in customer satisfaction, and 67% in product and service quality.
This makes the use of analytics and smart technologies to drive business performance the battle ground to compete on. It’s open to every business, and therefore those that take the lead will realise early, solid, and long-term gains and laggards may never make up that ground.
Choosing the right platform to drive adoption
Simply deploying technology is not necessarily enough to enact a culture shift. Many business intelligence solutions answer the same questions repeatedly and don’t go far enough to achieve a true data culture. As such, the technology used must be tailored to those using it with the agility to react to pressure situations and adapt to different users’ needs. In fact, the most impact is gained from technology that lowers the barrier to getting insights so that users are focussed on learning how and when to apply data, not on how to use data technologies.
Platforms infused with AI take this one step further, bringing automation and contextual information to encourage AI-driven analytics that provides the user with more automation and contextual information. This utility goes a long way in encouraging adoption, and in-turn, affecting the business culture and drives success in business goals.
One size does not fit all
Even when considering these elements, user adoption is often hard to predict. The users that are expected to adopt quickly can be reluctant – or those expected to be disinterested are the first users.
Often, this variation depends on how familiar and comfortable these individuals are with current technologies and whether new solutions are seen as an impediment or a help to their existing processes. If the benefits of using the new technology are clear, adoption will need less outside encouragement. While adoption can be hard to predict with variation between users, one thing is true: When clear business value is demonstrated, business users are motivated to adopt it to realise that value for their role, their career, and their business. This can materialise as actionable insight, reducing the time taken to complete tasks and freeing up the availability of the traditional analysts who would have previously been running data tasks for others.
As such, users must be able to recognise the individualised contextual value. For this, it is best to allow them to get their hands on the solution in question so they can begin to experiment and see how it can work for them. Firstly, clearly involve business users in defining use cases and problems that can be solved by data, so the business is building applications and bringing in technology they actually need. Secondly, show users what’s in it for them personally, either through examples of wins of their peers, career opportunities, etc.
The importance of leadership throughout
If the leaders of an enterprise are championing the cause of making data more accessible, then it’s only appropriate that they practice what they preach. Tools driving business insight and value should not be implemented in isolation. The tools are a part of changing how employees perform their roles, and may need to be supported by holistic changes to culture to reward the right mind-set and behaviours.
Executives need to practice what they preach. If they want to see adoption of data and analytics, they must adopt it themselves. They should include data to support decisions they make, ask for insights when approving a course of action, etc.
Other initiatives to consider revolve around ensuring employees understand how to use these tools. Training and reskilling can’t won’t happen without investment and a demonstration of their importance to the business. Further education and resources for upskilling users, organisations should also look at how they can create processes by which power users can partner with new users to help them learn and grow in confidence.
That research from HBR and ThoughtSpot revealed that 74 per cent of respondents who use analytics solutions saw long term increases in productivity when frontline workers are empowered to use the data at their disposal. Furthermore, 69 per cent said they’ve increased both customer and employee engagement, indicating that return on investment is achievable most in those who commit to using the solutions long-term.
In data and in analytics, the value of new technologies is tied to its level of adoption. Even with the best technology for the job and all the support possible from the C-suite, these technologies are contingent on actual users. By encouraging a company-wide culture that prioritises the end-user, you will drive adoption in your organisation and help it ultimately become more insight-driven – for greater success and growth.