I think we all can agree that these past two years have been ones for the history books. And if we’ve learned nothing else, it’s that we are all resilient. Amidst a global health crisis that upended everything from our personal lives to where and how we work to political and social unrest, we’ve persevered, changed, and adapted to a new world dynamics – that is here to stay.
Clearly, business is changing, too. It’s been disrupted in ways we never imagined. But throughout these dynamic times, one thing became clear: data is at the core of how we work. And analytics is the key to unlocking the value of data so your business can not just survive – but thrive – through changing times.
Unfortunately, though, too many businesses fail to go the last mile to turn their analytics strategy into an actual business strategy by ensuring that their business decision-makers have all the relevant information they need to be effective. In fact, it’s estimated that 70% of employees have access to analytics assets they shouldn’t have access to, while many other assets remain untapped by the teams that need them most. Further, less than 50% of an organization’s structured data is actively used in decision-making.
As we look ahead to 2022, it’s clear that our work to truly tap into the valuable resource of data and analytics continues. And as we close the books on yet another tumultuous year, we’ve spotted three trends that businesses now – and will continue to – face as we enter the new year. These trends will impact every business in one way or another and serve as opportunities where analytics will fuel work in ways we’ve never imagined.
For the last few decades, business leaders enjoyed an environment that was relatively stable and certain. Challenges were predictable – and largely surmountable. And environments were less volatile.
But we’ve now entered an era of uncertainty and dynamic change – an era that’s punctuated by an increasing pace of macro events that reveal new ways of organizing data and analytics with important impact on a business’ decision environment. An era where business models are changing and decentralizing, and where it’s no longer sufficient to use analytics to simply describe and diagnose results.
Consider, for example, the supply chain. Over the past few decades, companies emphasized a “just in time” strategy, which means keeping inventory to a minimum and using short-term, flexible partnership contracts that they could adjust quickly as changes in demand occurred. This strategy also moved production to low-wage locations, consolidated orders to maximize economies of scale, and minimized their physical presence in high-tax jurisdictions where possible.
While companies are not entirely abandoning their existing cost-minimizing supply chain policies, they are exploring alternative options to build more resilience at the expense of efficiency. Analytical insights are key to leading them through this learning exercise. The Financial Times recently reported on the emergence of this new “just in case” philosophy that focuses on three key principles:
All of these shifts come with new requirements for analytical capabilities to monitor and predict decisions related to their supply chain.
That’s why to succeed, today’s businesses need to be resilient so that as factors like supply chain breakdowns, the ongoing health crisis, digital privacy breaches, and political and social unrest persist, they can quickly adapt and pivot. They need to employ analytics to predict and prescribe so they can help their organizations not just navigate – but also anticipate – the rising tide of complexity and change. And businesses must continue to extend the equation of satisfying profit expectations for shareholders to other factors such as safety, health, environment, privacy, and brand by not just sustaining – but even predicting – the impact of these events.
During this time, the lion’s share of growth will be digital, where revenue is more real time, determined by customer satisfaction and sentiment and increased competition. To this end, companies must be able to read signals from all sides of the enterprise by empowering decision makers with analytical capabilities.
The global health crisis caused massive disruption for companies worldwide. Overnight, employees transitioned their workspaces from office desks to dining room tables. Supply chains fractured or came to a halt altogether. Teams became more distributed than ever before. And collaboration became even more vital.
As we enter 2022, companies will continue to explore new ways of organizing their workplace. For many, hybrid workplaces are becoming the new normal while others are electing to keep their workforce fully remote. In this new environment, collaboration evolves, too. Work will continue to be more distributed, collaborative (read: adaptive and cross-functional), and enabled by analytical capabilities. Cross-functional teams will come together for a purpose, using analytics to help them gain insight, solve challenges, and make decisions. These teams will then break apart, regrouping with others to solve different challenges.
But in this new environment, there is a shift in focus. As organizations become increasingly more complex, the focus shifts from volume to value. Instead of cross-functional teams adding to the report sprawl, leaders are challenging them to analyze what’s been created and utilize what exists, to understand the costs associated with creating new analytics assets, and to consider the full report lifecycle by knowing when to retire analytics assets that are no longer needed. Further, these teams are challenged to work in more agile ways by coming together for an outcome-based purpose and to use analytics in a meaningful way, rather than exacerbating the problem.
And that’s why I believe decision intelligence will become a key performance parameter in the future of work. Decision intelligence is the intellective skill base where advancements in the knowledge of how to use analytics to improve decision-making are made possible by the accessibility, quality, and currency of analytics assets to the business.
Sustaining a continuous flow and composability of analytics assets will enable trustworthy, meaningful, and actionable intelligence that will enable companies to explore business options and make small or large decisions across the board.
As responsibilities for decision-making become increasingly diffused across cross-functional reporting trees, mandates to procure and maintain data and analytics capabilities shift from a centralized CDO to functional leaders. And as decision-making changes to become more complex and uncertain – with calculations supplanting human judgment where possible using automation, AI, and machine learning – these functional leaders are the ones who ascertain that machine calculations are properly embedded and documented as automated components in analytics flows.
These new analytics leaders are not data scientists or even data experts. Instead, they are the consumers of the analytics assets. The ones who use them to make critical decisions. And the ones who need context and color in order to know which report they need for the job at hand.
These analytics leaders can’t wait for someone to create a report for them. Instead, they demand wide access to data and analytics so that they can drive the consumption of analytics assets. They govern these assets so that collective intelligence increases. And they confidently consolidate, reconcile, and reorganize these assets to reduce the noise caused by the proliferation of tools, reports, and other analytics assets around the organization.
As the new analytics leader rises, many companies expect CDOs to shift their focus from the data production pipeline to the analytics consumption pipeline. With an increased need for “all eyes on the ball”, functional leaders need to be more creative with exploring options that help the company as a whole thrive through uncertain times. Companies are supporting functional leaders by giving them an increased mandate for the procurement of analytics tools, education, and datasets. But at the same time, CDOs need to view these leaders as clients, and continuously redirect the data production capabilities to support their evolving analytical needs.
In addition, the lack of human capital caused by the Great Resignation further drives companies to transplant human decision-making with machine calculations. That’s why we’re seeing a rise of Robotic Process Automation (RPA) and Artificial Intelligence. These new capabilities will undoubtedly add on to the automated production of reports that companies need to discover and catalog.
Lastly, as the new analytics leaders rise, the data pipeline will change as well. Similar to how we saw data silos decompose into data pipelines that weave across business functions in the form of data intelligence in the 2010s, we now see a similar shift away from analytical hierarchies where analytics flows instead weave through key business objectives.
In 2022, the new analytics leaders – or flow leaders – will drive collaboration teams to discover, compose, and evaluate analytics flows around key work objectives. These flow leaders have existed implicitly but can now develop a new skill base through decision intelligence.
To address these trends, leaders in every industry must shift their thinking – from a traditional data governance model to an approach that encompasses complementary report and analytics governance. This approach will establish not just rules for data but also guardrails and safety measures that enable and empower more people to use data and analytics to create real value for their organization.
Getting there isn’t easy, but it’s possible. And to do so, leaders need three things.
First they need intent. Leaders must create a strong sense of future direction that transforms how they view data within the organization. They must see data and analytics as strategic – as a shareable and renewable resource. And they must infuse this thinking throughout the organization.
Second, they need innovation and transformation. They must encourage the adoption of new processes, structure, and technologies that aim to radically increase the analytics asset stock of the organization.
And third, leaders need to cultivate intelligence. They must create the intellective skill base, including distributive leadership and adaptive learning, to promote analytical agility and drive business innovation.
To address these three trends – and ones we cannot yet anticipate – organizations need decision intelligence. Decision intelligence enables leaders to choose the right options at scale, so their teams can navigate uncertain business waters.
ZenOptics supports companies to thrive in these uncertain business decision environments by maximizing the discoverability of the continuous stream of analytical insight across the organization, engendering new operational alternatives to existing business metrics, processes, and KPIs. To this end, ZenOptics focuses on the empowerment of flow leaders to transform their organization into the future of analytics-driven work.
So as we close the books on 2021, I encourage each of you to explore how decision intelligence can help your organization not just survive – but thrive – in 2022. You can learn more about decision intelligence by watching my keynote presentation from Differentia Day.
Ready to learn more? Register for our upcoming webinar on January 19, 3 Ways to Boost Your Analytics Action Plan Today.
Written by ZenOptics’ CTO Pieter De Leenheer