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Creating and leveraging trusted data helped organizations make sound decisions and execute on strategies that enabled them to response and recover in 2020, and respond in real time to market and operational challenges as they arose.  In 2021, as markets and economies stabilize, enterprise data operations will play a key role in revitalizing, reimagining, and driving growth.  

We foresee the criticality and maturity of Data Excellence increasing in: 

1. Fueling the Enterprise AI Agenda 

2. Enabling Increased M&A Transaction Activity

3. Focusing on Business Value 

4. Restarting and Accelerating Digital Transformations

5. Improving Core Data Operations

6. Automating the Enterprise with 鈥淣on-Traditional,鈥� IoT, and Sensor Data

7. Doubling down on Privacy, Security, and Sovereignty 

1. Fueling the Enterprise AI Agenda

Enterprises are counting on artificial intelligence (AI) to deliver optimization, value, performance, new capabilities, and increase options for B2B and B2C customers. More than 24% of companies with over 250 employees have invested in some form of AI.  However, AI and ML models are only as good as the data underlying them. CDOs, CIOs, and business leaders are now keenly aware that poor Data Quality is a key barrier to realizing AI aspirations. Data is at the core of AI and machine learning and without trusted, high availability data, businesses struggle to use AI and ML to unlock value.

2. Enabling Increased M&A Transaction Activity

As we move out of the pandemic towards economic recovery there will be winners and losers in each market.  This economic pattern has been consistent in the 鈥渂ounce鈥� following downturns, for over 100 years.  We expect to see this wave beginning to crest in 2021, with many companies forced to divest non-core business units or restructure, and others in an aggressive acquisition or roll-up mode.  These transactions鈥攎ergers, acquisitions, carve-outs, divestitures鈥攔esult in some of the most complex data projects that a business can face.  Organizations that excel at the data aspects of these transactions鈥揻rom setting up and managing data clean rooms, to integration, to post-transaction clean up鈥搑eap outsize benefits in time to value, risk and cost reduction, and realizing deal synergies. 

3. Focusing on Business Value 

The entire range of growth, cost efficiency, and customer/quality initiatives will come under tighter scrutiny to return quantifiable business value.  Executives will expect more  in the form of top line revenue growth, margin optimization, product/service quality improvements, and faster cycle times.  Targeted KPI improvements, business process reengineering, supply chain optimization/reconfiguration, sales efficiency, quality improvement, and customer excellence/customer satisfaction all depend heavily on Data.  With the growing realization that great market outcomes depend on solid metrics, Trusted Data, world-class Data Quality, high Data Availability, and thoughtful Data Strategies, executives鈥� focus on business outcomes will increase markedly. 

4. Restarting and Accelerating Digital Transformations

It鈥檚 been commonly noted that 2020 saw an enormous increase in the pace of Enterprise digitization.  Enterprises have been forced to respond to market and supply chain disruptions, and respond to customer needs more rapidly and flexibly than leaders thought possible.  The safety imperative of Remote work and Future of Work, in particular, has broken down entrenched change resistance and will continue to be a digitalization accelerant.  What鈥檚 less remarked upon but equally crucial, is that all these transformation initiatives鈥攂oth new efforts targeted to response/recovery and the doubling down on existing transformation agendas鈥攁re data-hungry.  Rethinking and reimagining the Enterprise via Digital Transformation is driving a value of data conversation that augers an investment wave in the full suite of both traditional and emerging Data Technologies and Processes.  

5. Improving Core Data Operations

Data Operations, consisting of an end-to-end, cross-enterprise set of business disciplines and technologies, including MDM/Master Data Management, Data Quality, Cataloguing, Data Interoperability, Data Governance, IPaaS and more, will continue to grow in importance in 2021.  DataOps is likely to become a more formally recognized core capability in enterprises as companies work to streamline their organizations and technologies to provide trusted, reliable data, everywhere, at high velocity.  Businesses addressing data with agility and control, based on good data governance and following the conceptual model of DevOps/Agile for code base management will position themselves to create meaningful competitive advantage through supplying clean, trusted data to analytics and decision support processes. 

6. Automating the Enterprise with 鈥淣on-Traditional,鈥� IoT, and Sensor Data

Unstructured data – images, video and sensor data are maturing and becoming increasingly important to automation and new-line digital products and services.  These range from more traditional real-time streaming, to processing of video streams to monitor pandemic mask and social distance compliance, to the automation and AI-enablement of white-collar tasks.  2021 will see more types of data integrated into workflows at higher volumes and unstructured data will increase in value and importance.

7. Doubling down on Privacy, Security, and Sovereignty 

With increasing regulatory scrutiny and awareness around the sheer volume of data that鈥檚 collected and stored about individuals鈥攊ncluding sensitive data鈥攆irms will continue focusing on retaining/restoring trust in data.  As consumers become more aware of the value of protecting their own private data, both enterprises and individuals will begin thinking more diligently about how they interact with an increasingly pervasive and powerful AdTech stack.  Traditional Enterprises will continue to deploy process technology solutions such as Customer Data Platforms that promise to 鈥渦n-disintermediate鈥� AdTech and restore B2C customer intimacy and access.  The importance of Data Provenance, Data Lineage, and Data Chain-of-Custody will all increase.