Leading with Data in difficult times

It’s rewarding to be ranked as a leader in Gartner’s Magic Quadrant for Data and Analytics Service Providers. In interacting with the analysts, we learn a lot about ourselves – and the way clients look at us – in terms of the completeness of our vision and the ability to execute. It’s also helpful to our clients, obviously, in selecting the service provider that fits best with their data and analytics purposes.

This happens to be the fourth year in a row, and obviously this year is different though. Organizations may have quite a few different things on their minds than exploring vendor rankings. Having said that, leading with data may prove to be more key than ever, in whatever mode an organization may be in responding to the pandemic crisis.

They may still be an initial response to the shock of the crisis – more than anything else to simply survive. They are more likely to be already involved in adjustment to what is destined to be the new normal for a considerable time to come. This may also include looking for cost-reduction & efficiency improvement. They may be planning for renewed growth in the renaissance after the crisis. And some may even be rising to the occasion: envisioning innovative business models that still seemed a bit too far-fetched and risky back in the good old days – you know, not so long ago at all.

One thing is for sure, technology – and data and analytics in particular – is a driving factor to any scenario. Almost any business – unless it was already 100% online and working virtually – will see its current IT infrastructure and data and applications landscapes pushed to the very limits. Numerous people are forced to work and collaborate from home, often on personal computing devices laptops that have not been designated for this. Access to mission-critical business applications is not a given, and the risks in areas such as data privacy and cybersecurity are almost too obvious to point out. Organizations that have not been exclusively delivering their products and services online, may be forced to quickly shift to digital channels as their main – or even only – route to market.

Response

It will make many organizations painfully realize that modernizing their IT landscape – including their data and analytics household – is long overdue. And although there may be plenty of temptation to lament on this, a ‘101’ basic set of fixing-the-core technology measures may be what is needed first. And it typically should be done at very short notice too, as this pertains to the very foundation of IT’s own Maslow pyramid.

Access to key data – particularly sensitive personal data – is restricted when working from home or other non-captive locations. This may block workers from performing their duties in critical support functions. Data masking and data virtualization may come to the immediate rescue here, as part of rebalancing the entire data landscape to reflect the new, much less centralized realities of having to manage Data Apart Together.

Over the course of time, technology has been used a lot to improve cost-effectiveness (2009, anybody?) and there are many opportunities in the current digital landscape as well. Clearly, making even more, real-time data available to the organization will be key to making informed, fact-driven decisions in terms of where and how to increase effectiveness. And the closer this data is infused in the actual business, the more power to the people there is, the quicker impact can be achieved. Furthermore, many implementations of more or less intelligent process automation- adding flavors of AI ”smart” to processes – have already proven their business case in the past few years – and there’s definitely much more out there.

Adjustment

Working from home, collaborating and creating online, delivering services and even products through alternative digital channels: we all knew it could be done. But it is obvious that the pandemic crisis is unleashing the full power of it, increasing its intensity day by day.

Online delivery of food and goods is surging, and customers are focusing on essential goods rather than lifestyle and leisure products. Many organizations find themselves in a pressure cooker to deliver much better, more compelling, and effective digital user experiences and the fine-tuned supply chain that is needed to deliver on it. They will definitely need to turn to real-time analysis of social media in order to understand the impact of the pandemic on consumer behavior and preferences and understand the new signature moments that are a result of it.

As the COVID-19 crisis spreads its footprint globally, organizations around the world are left grappling with issues of short or no supply of raw material, transportation disruptions, and manpower shortages. This does not only apply to the obvious areas in Manufacturing, but equally so to any other sector that heavily relies on its supply chain to deliver products and services to its customers. Established players in the supply chain may suddenly fall out, where other – previously unknown – partners may pop up. This leads to a delicate balance act between risk and opportunities, with little predictability of even the near future. It is critical that organizations, while responding with agility in the short term, also prepare for and take actions that ensure further resilience in the medium to long term.

In their latest pandemic research, the Capgemini Research Institute recommends short-term actions such as building visibility into the operations and vulnerabilities of suppliers and logistics partners, and strengthen cash flow management. It also advises to follow up with re-assessing customer demand, improving forecasts and aligning operations accordingly.

Much of this depends on the availability of high-quality data that is more real-time and is likely coming from more internal and external sources. With that, understanding and mastering the supply chain of data becomes just as important as that “other”, original supply chain. Furthermore, catering for a “Data Apart Together” reality where data can come from and go to many different stakeholders – some completely unannounced or unanticipated – will be often helpful; cloud-based data stores that are easy to set up, deploy and share might prove to be particularly effective. Organizations that find themselves in a continuous flow of ad-hoc requirements to safely – and transparently – transact with others in their business ecosystem may finally find a highly relevant case in applying a Blockchain platform. And then, when finally all of that data has come together, it may be up to the next generation of (AI) algorithms to detect patterns, forecast trends and recommend actions to determine how well the supply chain shock is dealt with.

Renaissance

Every crisis has an end, the pandemic will eventually go away. As this swan tends to be quite black, it is impossible to predict what business life will look after it. But that shouldn’t stop us from preparing for it. Organizations may simply look to reinvigorate what they already have been doing, aiming to quickly scale up again, and have their value chains up and running as soon as the opportunity arises. Others may find inspiration in the alternative digital channels and ways of working they have been forced to explore. They will reimagine and envision new, resilient business models – possibly AI-first, providing low- or no-contact experiences, featuring maybe even completely hands-free delivery as well. They may look to fully leverage the upcoming hyper-connectivity of 5G, the agile scalability of the Blockchain, or the next generation fluid workforce.

And indeed, some organizations are planning to industrialize what they originally set up as an improvised, bold use of technology. Alibaba, already known for its appetite for innovation, introduced a “resource leasing” model to share manpower during the crisis. They are now setting up a digital platform to enable this at scale and integrate the model into their ongoing operations, leveraging data and analytics to categorize and match employee profiles (such as years of experience, specialization, and roles).