Research (see box) shows how organisations that perform best financially are also ahead on data usage. Technology transformation provides data in ways that were impossible, even unforeseen, not long ago. When combined with business strategies that focus on customer engagement, this is massively greater in significance as we look forward, compared to 20 years ago when The Forum launched. Organisations such as Google, Facebook or Amazon are iconic, pioneering both in technical approach and culture.
Digital transformation can put the customer at the heart of what we do. Data can join up an organisation, it’s not just about the contact centre or a single department, and all kinds of enterprise are impacted. Take government or outsourcing, where service can drive the commercials. Or the ‘servitisation’ of manufacturing and IT, historically product-focussed or process-obsessed. Look at retail, at business-to-business – and the COVID-19 crisis is accelerating changes in behaviour too. You can’t compete fast enough in today’s world without joining up your data and effective business leaders understand this.
Digital transformation is driven by technology that provides data (‘digital’). Video, photos and voice are all searchable data. Machines can send us information about usage patterns and what is going on in or around us. They can alert us to issues that need action. Try searching the internet of things (IOT). Customers and colleagues can access all kinds of new information from mobile, smart devices and digital media. Field and branch operations can track everything people do. So, expect data to drive change in all departments, as it did in contact centres 20+ years ago. How will our siloed organisations be joined up as our work focusses on the end-to-end journey for customers? Data powers these changes. Data matters!
What does this mean for us and our operations? In the 2020 Awards, digital transformation runs across every kind of activity. We join up processes to manage them digitally, as in the L&G Back Office (pg 18). We transform the online journey for customers, as at Clarks Shoes (pg 36) and AA Ireland (pg 34) with chatbots & social. We join up data in our planning models, using operational or external inputs to predict customer and financial outcomes, as we have seen in RSA (pg 28) or LV= (pg 26). A capacity model proved transformational at Yorkshire Ambulance (pg 22) and we’ve seen the power of modelling in response to the Covid-19 crisis. Predictive analysis helps us focus on what we can influence or control and identifies gaps or disconnects, so that we can then prioritise the things that matter most.
Gartner’s maturity model
The potential impact for our work as analysts or managers is huge, as Gartner demonstrates (see graph). Looking back over 20 years, much of our analysis was ‘after the fact’, looking back to see what happened. If we used this for diagnostic insight, such as root cause analysis, we considered it advanced and, too often, this was for internal management purposes. Today, however, we don’t just look at what happened (descriptive) and why it happened (diagnostic). Increasingly, the best teams analyse what will happen (predictive) and take automated action (prescriptive). Furthermore, this goes beyond internal management usage, with direct impact on customer experience and business development.
If data is well connected, with data tags and good data dictionaries, it’s ideal for use in analytics or machine learning. At Openreach (pg 40), they search a vast database to trigger actions that optimise the work schedule and remove non-value activity, all automated. Moreover, data preparation and visualisation tools can automate dashboards and exception reports as at Legal & General (pg38) and, with speech analytics for Quality Management, at Vitality Health (pg44). Data automation and visualisation is gaining traction in our professional community as part of this movement and our PowerBi (virtual) networking group is set to be one of our most popular.
Start simple, think big
It can be easier to see the journey when you look back, as members do in entering our awards, and it’s instructive to look at past winners. ADT, in 2017-18, showed how a small amount of data can kick off major changes. The operation saved £1.9m in overtime, with 35% fewer service complaints. Data alone doesn’t drive this. Culture, dashboards and a demand-led resource model linked this to a wider service strategy. Since then, the challenge has been to scale insight capacity rapidly, as their value was recognised and requests flood in. Scale requires a different kind of data structure and analyst capacity. Likewise, the cross-company network of insight at Anglian Water (2018) demonstrates the power of joining up analysts to develop new fresh thinking and new approaches. And at Capita Innovations and The Times, the continuing journey of the insight/intelligence teams can inspire us,
as much as their original
Above all, our approach to change is crucial and it’s wholly different now, to the way we worked back in 2000. Build early successes, which can be high-impact with demonstrable benefits. Use continuous improvement to develop further with agile methods – such as ‘sprints’ and ‘scrums’ – rather than traditional programme management. We’ve seen that at RSA in the planning team (pg 28) and at The Very Group (pg 46), where a hand-picked group of advisors alternate between contact handling and agile process improvement. Why not consider everything we do as digital transformation, to be evolved in rapid stages with brilliant engagement? Data-driven decisions are so different in scale and scope now, compared to how they were looking back. Collecting data and performing analytics used to be prohibitively expensive, reserved for high-end businesses or programmes. Now cloud-based solutions make AI scalable and affordable. Bots can increasingly automate any routine, high-volume tasks, even in the planning team as at Sky (pg30). You can join up legacy systems and manage workflow. Auto-suggestion is familiar from Amazon or Google and increasingly planned in customer operations too. Think big!
Data-driven organisations perform better
- In 2019, research by Enterprise Strategy Group showed that data pioneer companies added 5% to revenues and cut almost 5% from costs. 93% say they make faster decisions than competitors. 60% far outstripped their customer retention goals (97% met their target).
- This backs up a 2012 Economist survey, which showed that 63% of companies who were ahead financially were also ahead on the way they used data.
- In the global ESG survey, 11% were data pioneers (21% in the technology sector), with low levels of dark data (stored but not utilised) and higher IT spend on solutions that investigate and act on data.
This article was first published in the 2020 Best Practice Guide - 2020 Vision: Crystallising your knowledge
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