Capitalizing on Life Science’s Head Start in the Race to Data-Driven
People and systems are the critical determinants of successful, sustainable data-driven operations. Are you prioritizing what matters?
The Life Sciences industry’s recent breakthroughs—redesigned ways of working, novel treatments launched in record time, and the reimagining of legacy sales systems—demonstrated the resilience of its organizations and hinted at the power of data-driven operations. We know that data-driven operations will enable the launch of breakthroughs, faster. We believe they will fuel partnerships, R&D acceleration, portfolio prioritization, and supply chain resilience. And we believe data-driven ways of working will power end-to-end engagement ecosystems, and expand the industry’s value proposition to include patient and HCP empowerment, community-driven co-creation, and new commercialized offerings. But the race to "data-driven" cannot be won with data alone. Life Sciences leaders must harness today’s unique confluence of digital know-how, reputational gains, and operational resilience to capitalize on the promise of a data-driven future. Discover how Life Science organizations can empower their people and systems in ways that maximize blockbusters, increase speed to breakthrough, and minimize risk by reading the blog below. The piece outlines the critical determinants of a data-enabled organization: a human-centered data strategy; transformation efforts driven end-to-end by insights; data-centered workforce capabilities; and a culture that lets data lead.
Harnessing Policy Pressures and Financial Positions to Power Future-Readiness in Health and Human Services
Flush with funding and still recovering from pandemic response “what ifs,” state HHS agencies are uniquely positioned to realize the potential of data-driven operations.
Interoperable, cross-agency, data-driven operations have emerged as a promising panacea for disparate health outcomes, missteps from maxed-out social workers, and challenging shifts to value-based payment models (VBP), among others. Yet tack-on tech and insights alone do not create outcomes-driven, interoperable, whole-person health ecosystems. Moreover, legacy processes, territorial silos, digital deficiencies, and evolving federal and state rules and regulations create significant barriers to establishing data-driven operations. In the blog below, we define the critical determinants of getting data-driven—a human-centered data strategy; transformation efforts driven end-to-end by insights; data-centered workforce capabilities; and a culture that lets data lead—and provide actionable ways for HHS agencies to assess and prioritize them. With funding in the balance and federal administrative shake-ups on the horizon, HHS agencies can use these insights to maximize today’s unique confluence of incentives, mandates, and a momentum of change to fuel a future-ready transformation.
Unlocking the Power of Data in Transportation
As the transportation industry continues to grow, the importance of data does, too. How can transportation agencies make the most of this opportunity?
As we look to the future of transportation, we see a world of innovation where connected and autonomous vehicles (CAVs), smart cities, vehicle-to-everything (V2X) communication, smart mobility solutions, and intricate back-office and enterprise resource planning (ERP) systems coexist. And with the advent of light detection and ranging (LiDar)/Internet of Things (IoT)/Telematics data collection, the volume of data that transportation organizations possess is rapidly expanding. In 2021, the transportation industry accounted for a staggering 8.4 percent of the US Gross Domestic Product, amounting to $1.9 trillion. Furthermore, the data and analytics (D&A) market within the transportation industry is flourishing, with a compound annual growth rate (CAGR) of 16.5 percent, and projected to reach $71.8 billion by 2032. Clearly, data has become one of the industry’s most critical strategic assets. But much like physical assets such as roads, bridges, and freight, data must be managed, maintained, and harnessed to reap its full potential. In our new blog below, we define the critical determinants of getting data-driven—a human-centered data strategy; transformation efforts driven end-to-end by insights; data-centered workforce capabilities; and a culture that lets data lead—and provide actionable ways for Transportation agencies to assess and prioritize them. Discover how Transportation agencies can better meet today’s ambitious goals while embedding the data-driven, digital dexterity needed to deliver on the next set of generation-defining endeavors.
Establishing a Data-Driven Defense in Emergency Management
Data-driven operations enable Emergency Management organizations to respond more effectively to today’s emergencies while building an operational infrastructure for the future.
Prior to 2020, no one thought a crisis manager would be the point person for a healthcare-related pandemic. Or cyber-attacks. Or a mental health epidemic. And yet Emergency Management organizations have become the default responders to a spinning kaleidoscope of crises—all while the frequency and cost of natural disasters and workforce burn-out are on a meteoric rise. Due to the need to remain compliant with regulations and standards, as well as the ongoing pressure to respond quickly and transparently to an ever-increasing number of crises despite limited resources, Emergency Management organizations have been forced into reactive ways of working. However, an increasingly complex, unpredictable, and interconnected Emergency Management storm is raging ahead. Without immediate steps toward data-driven operations—taken precisely, and in ways that don’t disrupt day-to-day crisis mitigation, response, and recovery— Emergency Management organizations will soon find themselves underwater. In the blog below, we define the critical determinants for becoming data-driven—a human-centered data strategy; transformation efforts driven end-to-end by insights; data-centered workforce capabilities; and a culture that lets data lead—and provide actionable ways for Emergency Management organizations to assess and prioritize them. Data-driven organizations aren’t made by data alone. The insights in this piece will help Emergency Management organizations maximize data gathered before, during, and after a disaster, and leverage each crisis as an opportunity to grow digital dexterity and cultural know-how.
Making Good on the Promise of Data-Driven Healthcare
In the value-based healthcare ecosystem of the future, data-enabled operations will define the providers and payors of choice. In this post-pandemic environment, are you on the right track in the data-driven race?
Technology and insights promise healthcare organizations optimized processes, increased revenues, personalized treatments, and automated everything. They promise more breakthroughs, better outcomes, and deeper engagement with patients. Yet record-breaking investments in tech and digital—the healthcare industry spent nearly $30 billion in digital acquisitions in 2021—largely failed to make good on those promises. While ushering in essential telehealth capabilities, the tech rush also layered workload and stress on healthcare employees. And most critically, it didn’t embed data-driven, digital dexterity at the operational core of most healthcare organizations. Here’s why: Tack-on digital investments aren’t enough to drive cultural change. And more data, just for data’s sake, is potentially damaging when the input burden is put on an already overtaxed workforce. In our new blog, “Optimizing Your Position in the Race to Data-Driven,” we define how healthcare organizations can make technology and insights work for them by prioritizing the critical determinants of a data-enabled organization: a human-centered data strategy; transformation efforts driven end-to-end by insights; data-centered workforce capabilities; and a culture that lets data lead. This piece will help healthcare organizations capitalize on the collaborative, continuous, and cost-saving promises of operational digital dexterity, and claim a leadership position in the rapidly evolving healthcare market.
Next-Stage Digital Transformation in Financial Services
Think safeguarding and cutting costs during recessionary times is the right approach? Research says otherwise.
Recessionary pressure often means financial service organizations ‘go-to’ position is to safeguard and cut costs. However, research shows that the companies that emerged from previous recessions as industry leaders did the opposite: As the economy cratered, they accelerated investments in initiatives that mattered, doubling down on the capabilities needed to capitalize on a post-recession economic upswing. Overwhelmingly, research shows finance leaders believe technology and insights are what matters, both today and in preparation for our economic future. And they’re right, however, the rules of digital transformation have changed. The difference is human, and our new blog below outlines how organizations can gain future-ready digital dexterity by prioritizing the critical determinants of a data-enabled organization: a people-centric data strategy; transformation efforts driven by insights; data-centered workforce capabilities; and a culture that lets data lead. As they lean into technology and data, this piece defines how leaders can harness their greatest asset—human capital—in pursuit of seamless compliance, increased automation, data, and operational agility.
Retail’s New Course in the Race to Data-Driven
The people-centric transformation activities required to capture data-driven value now and embed digital dexterity for the future of retail.
While the retail and consumer packaged goods (CPG) industries may be the first to feel a recession, they are likely to be the first to recover. However, this assumption comes with a huge “if”: Recovery and future leadership are only attainable to the organizations that double down now on the capabilities needed to capitalize on a post-recession upswing. Those capabilities are enabled by technology and insights. Every aspect of retail and CPG operations—from workforce management and omnichannel customer experience, to supply chain optimization and operational adaptability—is made better, faster, and more profitable with digital dexterity and data-driven operations. But just as everything about how the retail industry operates has changed post-pandemic, so too must the way we approach digital transformation. In our blog below, we explain how organizations can realign their transformation activities to capture data-driven value now and embed digital dexterity for the future. To blend data-driven insights with human instincts and meet customer needs with digital dexterity, the retail and CPG industries must prioritize four critical determinants of a data-enabled organization: a people-centric data strategy, end-to-end insights-driven transformation, data-centered workforce capabilities, and a culture that empowers data.
Optimizing Your Position in the Race to "Data-Driven"
For years, we have consistently advocated for leaders to adopt a more data-driven approach to steer their organizations toward success. That assessment has never been met with much resistance, but it also hasn’t been met with much action.
And that has largely come down to data “know-how,” or the knowledge, skills, and capabilities to transform data into valuable insights.
In the current business landscape—characterized by rapidly changing customer and workforce expectations, as well as unprecedented market, societal, and environmental considerations—the need for companies to become data-driven has become more urgent than ever. Data has the power to help leaders and teams make informed decisions, spot trends and opportunities, understand customer and workforce behaviors, mitigate risks, and drive positive outcomes and growth. For these reasons and more, delaying action in the race to “data-driven” is no longer an option for those who seek to stay ahead of the curve.
Global workforce challenges persist, and new ones arise. Enterprise commitments to operate with greater diversity, equity, and inclusion (DEI) require businesses to reflect, make different choices, chart a new path forward, and intentionally measure progress along the way. And faster than ever, organizations face ongoing pressure to do more with less due to the constant threat of recessions. These factors present never-before-seen challenges and opportunities—ones that demand flexibility and adaptability.
This places a new mandate on leaders: Don’t double down on everything, but be prepared to accommodate anything. To meet this mandate, data is the single reliable tool that leaders can trust to guide them through uncharted territory.
But the race toward becoming data-driven cannot be won with data alone. To compete, an equally pivotal success factor is the ability to effectively harness data through internal know-how.
Take a page from tech
Workforce technology know-how has long outpaced peoples’ ability to tap into data and produce actionable insights. Bias, bad data, and distrust caused missteps, and technology widened its stride.
Drafting off technology, many organizations (particularly those that grew into success quickly) didn’t pause to invest in their data capabilities. And up until this point, organizations have grappled with inadequate or poor-quality data, which made the transition to a data-driven approach seem daunting, impractical, and ineffective.
But the tides have turned, and we now have access to robust, dependable data that is easily accessible to all stakeholders, and not just designed for end-users. Many organizations are now equipped with advanced technology and tools that enable them to collect, analyze, and interpret vast amounts of data from a range of digital channels. Additionally, leaders are increasingly recognizing the importance of data-driven decision-making in navigating challenges and disruptions related to the workforce, economy, and more.
And as a society, we’ve been training. Ubiquitously, even unconsciously, we’ve been gaining speed and maturing our abilities to interpret and activate data in absolutely everything we do.
After all, technology and insights have become the metronome by which the rhythm of our everyday lives is set. Our parents use them to connect and receive care. Our society, and especially our children, increasingly rely on technology and data-driven insights to facilitate various aspects of their lives. Technology, for instance, is now a ubiquitous tool for learning, communication, and entertainment, while the concept of success has expanded to include metrics such as online engagement and popularity, exemplified by the use of social media "likes" as a means of measuring one's influence or impact.
As data increasingly becomes democratized, the potential for organizations to empower their people and systems in ways that optimize energy expenditures, increase speed, proactivity, and predictability, minimize risks, and reduce operational drag have never been more attainable. Below, we explore exactly how to capitalize on this opportunity by building data know-how.
Put people at the center of your data strategy
Until recently, the concept of a data-driven organization—rife with robots, human-less workspaces, and autonomous everything—felt more science fiction than mission-critical. Then a global pandemic fast-tracked our personal adoption of sci-fi tropes and converted digital novelties into operational necessities.
The technology that props up those robots, human-less workspaces, and autonomous everything are readily attainable. But most organizations aren’t prepared to empower those technologies with the data and insights that generate value and propel them strategically forward.
Here’s what most organizations get wrong: Data collection and insight development is still a very people-centric job.
Tech-empowering, human-inspiring insights don’t come from machine-generated data alone. They stem from an amalgamation of anecdotal, dynamic, and automated sources, and rely on a digitally fluent workforce for successful execution. Becoming data-driven is less about the technology and data and more about the capabilities and know-how of your people. When your employees are skilled at contextualizing data, they can make confident decisions and foster trust throughout your organization, which is a key ingredient to growth.
How to Move from Science Fiction to Reality:
- Get real with how ready you are. A comprehensive assessment, blending subjective and objective data from across your workforce, workplace, and ways of working, provides the required context against which transformation strategies can be developed.
- Hydrate your data lake. Conduct a data health "checkup" periodically to define (or redefine) the data your organization requires and ensure that it has the appropriate attributes to be relevant and valuable.
- Connect your people to the process. Make data the primary means through which everyone's job can be simplified and streamlined. Prioritize building a culture that values collaboration across silos and enables the adoption of robust practices and platforms to facilitate holistic data collection and insight generation. This will position data as a tool that can enhance the effectiveness of everyone's job, rather than as an additional responsibility or burden.
- Make data upskilling a priority. To fully leverage the benefits of data-driven decision-making, it’s critical to prioritize data literacy and fluency across all levels and functions in your organization. In other words, create opportunities for employees to learn about data and develop their skills on the job. This could be done by creating dedicated time and resources for employees to learn and experiment with data, or it might mean setting aside time for employees to attend training sessions, workshops, or webinars focused on data analytics and interpretation. It could also involve encouraging employees to experiment with data in their day-to-day work (i.e., analyzing customer feedback, tracking website traffic, etc.). In addition, organizations can integrate data into their Learning & Development (L&D) programs to ensure that all employees have the skills and knowledge needed to make data-driven decisions. This might involve creating specialized training modules or courses focused on data literacy and fluency, or incorporating data analysis into existing training programs. It's important to note that data upskilling is not a one-time event, but rather an ongoing process as the organization's data potential increases. Therefore, organizations must be intentional and consistent in their efforts to promote data literacy and fluency across the organization, and continuously evaluate and improve their data training programs to ensure they remain relevant and effective.
- Trust your people’s intuition. Establish the structures, tools, and training to standardize employee-led sanity checks designed to weed out biased or dirty data and round out insights.
- Foster a symbiotic relationship between your workforce and your insights. Prioritize the insights that level up individual roles into decision-making, higher purpose, data-generating functions. Additionally, encourage (and make the space for) your workforce to identify and consume data in ways that generate value.
- Seek insights in full color. Data is good at telling the truth about one moment in time, in one small slice of a dynamic system. Companies must expand that aperture of truth to move beyond black-and-white, moment-in-time data to full spectrum, full-color insights.
Harness data and insights across your end-to-end transformation strategy
Organizations worldwide spent $1.8 trillion on efforts to digitally transform business practices, products, and organizational structures in 2022. On average, we know that about a third of those investments—$600 million—failed to meet goals and generate value.
The ways organizations are becoming data-driven simply aren’t working, and our recent research spotlights at least one reason why: While data and insights are often used to inform an initial strategy, companies aren’t harnessing the power of data across the end-to-end transformation journey.
The irony is this: Organizations need good data and insights to become data-driven. Good data begets better data; better data begets precise insights; and precise insights beget efficient, proactive, valuable, and lasting change.
How to Overcome the Irony of Data’s Role in Advancing Data-Driven Transformation:
- Enable employee capabilities and capacity. Identify and automate commoditized tasks to free your employees’ capacity. Then reskill, upskill, and activate those employees to support the development of insights that are high quality, trustworthy, and continuously generated to inform strategic pivots and progress across a transformation journey.
- Build monitoring and measurement into the project plan. Seamlessly integrate these reflection points in ways that facilitate continued forward momentum and prevent blind implementation. Utilize a tool that ingests data from various sources to generate insights that can be monitored and measured.
- In lieu of historical context, lean on traditional data-gathering methods. You are building something completely new, and there is no historical data against which to judge progress. However, other valuable data and insights are there for the taking. Consider bringing quantitative data to qualitative conversations and interactions for a deeper understanding of what drives behaviors, perceptions, and motivations. And while you wait out data’s journey to becoming more accurate over time, employ traditional feedback and insight development methods to establish customized baselines and measurement tools.
Don’t skip critical developmental milestones
Artificial intelligence (AI)-powered automation and innovations, like ChatGPT, are irrefutably compelling. Yet for most organizations, the application of automation should be less compelling and more commoditized. At least for now.
Before large-scale AI investments, companies must get good at the foundational determinants of a data-driven culture. They must develop the workforce capabilities to produce near-perfect data and bespoke insights, and the cultural trust to let those insights lead. And they must weave data-driven practices into every aspect of decision-making and strategy development in ways that are normal, not novel. After all, access to data empowers companies to identify the most relevant, beneficial, and supportive trends for their overarching mission.
How to Establish Digital Connective Tissue, Not AI Band-Aids:
- Enable your leaders to move from thinking to knowing. A data-driven culture starts at the top, with leaders who practice and expect data-driven decision-making. Quality data enables leaders to move from thinking to knowing, promoting data-driven norms. And the potential of data-driven knowing is personal for leaders: Data empowers leaders with reliable decision-making, reducing bias and safeguarding their position and the impact of their choices. However, embracing the shift to data-driven knowing also requires leaders to seek and provide proof. For instance, in the context of returning to work, relying on assumptions rather than data can create significant issues. Leaders who backtrack on previous declarations are often forced to do so when data reveals that their ideas are not feasible. Thus, incorporating data-driven decision-making is crucial for effective leadership in today’s environment.
- Prioritize adoption over change. Six in 10 IT leaders say they’re concerned by slow end-user adoption, and how it endangers the return on investment. Maximize ROI with robust monitoring and management practices focused on the degree to which employees have embraced the behavioral and technological drivers of data-driven transformation.
- Automate rote, manual tasks to free human capital. Whether that work entails data strategy and insights development, as noted above, or management and decision-making, your ability to create more purpose for your people will directly correlate to enterprise growth and lay the groundwork for the expansion of automation in the future.
Just as our know-how has evolved, so too must our understanding of the true value of being data-driven. Yes, it’s the key to understanding and serving your customers and employees. Yes, it will optimize and automate rote systems and processes. But most importantly, becoming data-driven enables people and organizations to adapt to change. Prioritizing adaptability—not digitization for digitization’s sake—will fundamentally shift how companies plan, implement, and measure their data-driven transformations and keep pace with technology in the curves ahead.