It’s no secret that transformation is risky. For many, this risk outweighs the benefits of inactivity; McKinsey found that the rate of successful digital transformation is consistently low, with only 16% finding success over the long term.
Within industries and business sizes, this also varies. Businesses with fewer than 100 employees are almost three times more likely to have fruitful transformational efforts compared to businesses with up to 50,000 employees. For those on the larger end of town, not only is the undertaking significantly more challenging, it is risky enough to see their business fail long before it would from natural attrition.
One of the reasons why digital transformation carries such risk is there’s no standard. You can’t purchase an out-of-the-box model for digital transformation that simply plugs in and is ready to go. Problems come in two categories: those that are well-known and have been solved before, and those where the work still needs to be done.
Digital transformation is the second. It’s breaking new ground and has typically not been done before, posing a unique challenge that requires an experimental and unfamiliar approach. For it to happen effectively, you need to be truly on top of change management to keep it heading in the right direction, using data.
Putting process into practice
The essentials for effective digital transformation still need to be in place before starting on the change management path. You’ve got to learn how to walk before you can run. The fundamentals of leadership, vision, and data capability are essential foundations ahead of taking the next step and adding another layer, providing the guidance to put an effective strategy in place and oversee the whole process.
From there, you need to add a data-driven change methodology. This is more than a traditional change-management approach, which emphasises training, messaging, and champions. It introduces a performance feedback loop to actively track progress and change course accordingly so all action is actually substantiated.
To start, you have to identify the driver of value for each initiative. We typically uncover these during the Domo Business Value Assessment, when we look at what is going to actually drive the value, such as higher conversion rates or reduced wastage. From there, identify the metrics—how do you measure it, what data do you need, and what visualisations are required? It’s through metrics that you can figure out if the driver is going in the right direction, such as if the conversion rate has improved from 1.0 to 1.5.
Look at the metrics every day, or at least every week week. If things aren’t moving the way they should be, then make change—that’s the monitoring part.
At the core of the feedback loop is a team working to drive your key metric. People must be engaging to drive change in the right direction, whether it’s through regular team meetings, a shared dashboard, or other data collaboration tools like Domo.
New South Wales customer service minister Victor Dominello has already implemented data-driven change management with great success. Initiatives like the CTP Green Slip refund are all tracked in Domo against metrics that actually drive success, and are checked daily, if not hourly. If something is out of line, action is taken to correct it in line with the metrics. Rather than being a one-off, this is now the principal behind all change and progress within the agency.
Data-driven change management is a natural bridge between value assessment and momentum. Through Domo, we can map what drives value, develop use cases, and create a plan that is fully measurable in real time to manage this essential change for your business.