Leading manufacturers are increasingly transforming into hyper-efficient value-added service providers. Those who are doing so most successfully not only understand the value of their data, but also see it as a strategic asset.
With the proliferation of data, how can you understand, curate and utilise your data to enable transformative business decisions and accelerate digital transformation?
It is fundamental to understand the value of your data, the whereabouts of your existing data assets, how to govern it, and make it accessible and widely available across the business.
A discussion session held as part of Manufacturing Innovation Summit 2020 explored best practices to help manufacturers learn how to achieve a data-driven digital transformation.
Moderated by The Manufacturer, the session had expert insight from Greg Hanson, VP EMEA for Informatica, and Giovanni Milani, a Senior Director for Cognizant.
Building your data strategy
The key to creating and deploying an effective data strategy comes down to three factors: sponsorship, a standardised platform and robust governance.
Sponsorship is vital, according to Greg Hanson, particularly in larger organisations where buy-in can be more difficult to achieve.
“Additionally, the successful deployment of that strategy requires engagement with the organisation as a whole, and a cultural acceptance of responsibility regarding data given GDPR and privacy laws,” he added.
Helping to drive this combination of board-level sponsorship and enterprise-wide engagement are Chief Data Officers, newly-created executive roles tasked with deploying and monitoring the effectiveness of data strategies and the adoption of modern, cloud-based architectures – the foundation of many industrial digital transformation initiatives.
“There are so many technologies readily available in the cloud space now that companies face the risk of ‘cloud sprawl’ which degrades the impact of their digital transformation and data management,” Hanson continued.
To avoid such a situation and simplify their approach, Hanson recommended businesses standardise on one AI-based platform, one that can offer everyone access, but with a “different lens” on the data depending on their role.
“Finally, good data and process governance helps assist the creation and maintenance of high-quality data assets and enables the self-service of data within the organisation. That’s what really drives transformational outcomes,” he concluded.
Avoiding the common pitfalls
To start with an example, a frequent issue arises when taking a digital project from the testing environment into the real world; the real benefit comes from the combination of technological innovation with process transformation and people considering the true end-to-end process.
According to Giovanni Milani, managing “paradoxes” is key to a successful digital transformation and these paradoxes are multiplying.
Examples include aspects such as the approach to process innovation with bottom-up continuous improvement versus top-down disruptive design thinking, whether to store data locally in ‘puddles’ or off-site in large data ‘lakes’, realigning organisational responsibilities across business silos, or even the choice between micro, localised production sites versus monolithic mega factories
“Those driving your digital transformation strategy may come up against objections from different business units. A local process lead can often have very different objectives and targets from a business lead.” Giovanni noted.
“Ultimately, these decisions can’t be made in isolation. Alignment of the business, with everyone incentivised to pull in the same direction is fundamental to what you’re trying to achieve. Hence the great success of founder-innovators like Elon Musk, Rolls-Royce, Dyson and many others”
“Take the use of production line robots in the automotive industry as an example. Initially, the robots were expensive, cumbersome, inflexible and had to be fenced off. Now, you have agile, highly flexible, affordable ‘cobots’ that can truly work alongside people.
“It’s the integration of automation with people, not replacing one with the other, that actually delivers transformation. And the same evolution that has happened in physical automation is happening in digital automation.”
Creating tangible business outcomes
As with any business improvement project, your organisation’s digital transformation must correlate with your overall mission statement, with clear measurable outcomes and ROI.
These objectives may be environmental, financial, efficiency, portfolio diversification, market growth or quality driven; regardless of the specifics, it is blatantly evident that huge value to reaching objectives in new ways lies in the data, structured or unstructured, that is spread across our businesses.
Data coupled with digital technologies provides insight and enables you to achieve those goals faster and more easily.
Aligned to that is the pressing need to link value and delivery early in the process, focus on achieving one goal, deliver it swiftly and use that momentum to move on to the next one. This will enable a swifter change management and alignment of priorities across the business.
Greg Hanson noted that there two ways to achieve return on investment (ROI) associated with data – tactical and strategic.
An example of a tactical approach would be data cleansing associated to a specific application or data store such as those that support outbound marketing or customer relationship management (CRM).
A tactical deployment of data quality technology can quickly demonstrate ROI by removing duplicates and improving general data quality which in these examples would result in better campaign response rates, better ability to cross sell / upsell and improved customer experience.
A strategic approach typically involves adopting a standardised platform and employing good data quality and governance across the data landscape. It also involves specialised people such as data engineers and/or scientists, who can more easily derive the full value from a company’s data.
“These individuals cannot be siloed,” Hanson noted. “What works well is having a buddy system that links those data experts with department heads and team leaders in order to ask the right questions of the data.”
Giovanni recalled a conversation he had with the CEO of a municipal utility company who noted he had more information than ever before but didn’t feel that he was taking better decisions than 30 years ago:
“That’s an example of another paradox, we have access to enormous amounts of data, but which data is useful and how do we then link that to our overall digital strategy?” Giovanni commented.
“The secret is to start with a small, simple project, that’s aligned with your company objectives and creates value, financially, culturally and organisationally. Some businesses have managed to create new types of governance, stretching from data and data factories through to digital innovation councils.”
- There are many differences between one company and the next but there are also a great many universalities, one of which is that the value of data is undeniable and fundamental.
- Having a grip of Data, Technology and Systems is indispensable table stakes, but not sufficient. People and culture are just as vital to its operational success.
- So, starting with the right people in the right place is as important as where you collect the data.
- Though you should start with small steps, the greatest value and chance of success lies in adopting an attitude for ‘digital at scale’ along a business process, not in silos. Data mining coupled with Subject Matter Experts can help get that end-to-end process perspective
- Make sure there’s a clear and measurable business case, ROI and strategy to get there. Like many visionaries, you can start with a back-of-the-envelope estimate.
- Sponsorship is something to get right from the start, from the boardroom down to the shop floor – you’ll struggle to achieve the right level of cultural engagement without it.
- Keep things as simple and user-friendly as possibly, consider the user experience and avoid complexity.
- It’s an advantage to have as much data as you can afford to have stored in the cloud because ultimately a high level of granularity will offer you more and deeper insights.
- Where possible, democratise data. When you put data in the hands of talented, motivated people who have business outcomes in mind, that’s when you really translate data into tangible value.
For more insights and to have a more in depth conversation, please contact Greg Hanson and Gio Milani
*All images courtesy of Depositphotos