Government Empowered Through Digital Transformation

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1 Government Empowered Through Digital Transformation Adelaide O Brien IDC IDC

2 Government Empowered Through Information DX 1 2 Information Digital Transformation Stages of Government Deployment of Big Data 3 AGENDA 4 Challenges Ahead Essential Guidance 2

3 Digital Transformation is Multifaceted The Five Key Areas of DX Leadership DX Omni- Experience DX WorkSource DX Operating Model DX Information DX 3

4 Information Digital Transformation Big Data for better decisions, optimizing operations, and providing appropriate services and information. Incorporate advanced and predictive analytics, using machine learning and cognitive systems for real-time access to data to Improve efficiencies Enhance security Prevent bad actors from doing harm 4

5 Stage of Organization U.S. U.S. Federal Government Deployment Deployment of Big Data of Big Data Q. At what stage is your organization today in the deployment of Big Data? Not Yet Considering Considered Researching 34 Pilot/POC In Production in BU In Production Enterprisewide % Federal Responders Source: 2017 Industry IT & Communications Survey, IDC Customer Insights and Analysis, April, 2017 N=70. 5

6 Big Data Thrivers vs. Survivors Thrivers are 3X as likely to have executive leadership strongly emphasize a datadriven culture and mandate the use of data, analytics, and technology. Thrivers are 6X as likely to have enterprise-wide skill sets. 6

7 Big Data Thrivers vs. Survivors Thrivers consistently integrate one or more types of data for analysis: Structured transactional data (e.g., benefit payments) Rich media (e.g., video, audio, and images) Web clickstream Geographic or spatial data Mobile device data Chatter or text from social networks Customer interaction s, notes Text from content repositories Sensor data or machine generated data 7

8 Big Data Thrivers vs. Survivors Thrivers are twice as likely to have known, governed and well understood data definitions and lineage. Thrivers are 5X more likely to have all relevant internal and external data at necessary granularity. Thrivers are twice as likely to have data quality addressed enterprise-wide with ongoing monitoring, correction, measurement, and proactive issue prevention. 8

9 Data Quality is Important for AI AI and cognitive go beyond Big Data to learn and reason, and are the next step in bringing new layers of intelligence in analyzing unstructured and semi-structured data. AI systems typically make decisions based on data-driven models created by machine learning. Machine learning depends on data, lots of data. 9

10 Challenge: Benchmarking Remove the Deployment Scare Factor of in Big Information Data and DX Analytics in Government Especially AI and Machine Learning Supports Humans Making Data Driven Decisions

11 Challenge: Support Multiple Key Roles in Information DX Project Managers Domain Experts IG CIO Project Managers Data Scientist LOB 11

12 Challenge: Ensure Privacy and Security CIOs play an important role in helping business leaders understand that AI has profound implications for privacy, and security. Governance models should address data quality, performance, interoperability, usability, security, and privacy. 12

13 Essential Guidance: Enable Data Driven Decisions How are you providing transparency of AI based decisions? Do your data governance policies protect PII as AI connects troves of data? Are your analysts still making data calls? What is the quality of your data? How are you measuring progress? How are you supporting analysts and data scientists? 13

14 Adelaide O Brien Research Director aobrien@idc.com Have you joined our IDC Community for analysts blogs? Sign up for our free monthly newsletters: 14