Big Data & Analytics Competency Center at the Chief Digital Office

The Big Data & Analytics Competency Center at the Chief Digital Office is dedicated to helping digital executives use big data and analytics to transform their firm’s relationships with people. It features reports, thought leadership, presentations and other assets that focus on envisioning, planning and pursuing new-generation data initiatives that provide the insight to serve people in new ways and launch new offerings and revenue streams. The Chief Digital Office has competency centers in social business, mobile, ecommerce and big data.

Point of View

“Big data” is a simple concept to grasp, but making it work requires finesse and commitment. Paradoxically, for most firms, the route to success begins with optimized investments in “lean data,” a quick, light, iterative process of testing and adjusting to prove business value before scaling.

Vision: Where do we start?

Most firms have been collecting transaction, marketing, service and other data for decades, but they’ve made relatively little use of it because computing has been so costly. Today, the Web, social networks, smart devices and public, “open” data are exploding the variety and amount of data available to firms, and big data strives to turn data into insight by leveraging modern hardware, software and analytical tools. Analytics are sophisticated algorithmic tools and processes that evaluate transaction, web, demographic, location, social, mobility, temporal and myriad other data, and they display results in easy-to-use visualization tools. However, big data often involves large, slow-cycle I.T. investments as well as significant culture change in data analytics departments and management. The best way to start is working with high-impact (often) unstructured data.

Strategy: How do we learn what we really need to delight customers?

Firms can use a “small/lean data” approach to mitigate big data investment risks. First, maintain a constant focus on the ultimate goal: using data to empower the firm to create breakthrough experiences for customers and other stakeholders (“users”). Second, define and rank users in importance to the firm, and analyze digital social platforms (“venues”) to determine the desired outcomes of the firm’s highest priority users (when they use its products and services). Once you know and validate users’ critical outcomes, you know what kind of data to collect and use. Third, create a social business strategy that specifies the optimal venues in which you can engage users and what kind of data will enable you to help them reach their outcomes more easily.

Execution: How do we invest while mitigating risk?

The social business strategy will recommend several pilots that will test the strategy and teach the firm’s team(s) how to use data to maximize their ability to help users reach their outcomes, thereby “adding value” to the use of firm products/services. Rather than an I.T.-style requirements analysis, firms use social venues to test, validate and adjust strategy in short cycles. By creating and focusing on data that improves user outcomes, and by using the data in their interactions with users in social venues, they can optimize their big data investments.

The key to succeeding with big data is an unwavering focus on improving user outcomes in situations that involve firm products or services. It’s the secret to delivering breakthrough experience, time after time.

CSRA on Big Data/Digital/Transform

My latest thinking on big data/digital transformation:

The CMO Guide to Big Data and Analytics

Chief Digital Officer Needs Analysis

CIO Guide to CDOs and Digital Transformation: How to Adapt and Thrive

Why Probability Is the Key to Profit in the Digital Social Big-Data Age

Omni Channel From Brand and Agency Viewpoints: DAA Chicago Symposium

Digital Transformation’s Personal Issue

Big Data in Healthcare and Education

Omni-Channel Retail Mobile and Big Data

All CSRA posts on big data/digital transformation.

Big Data Opportunities

Teams using new technologies like big data usually fall into the tech trap; they scope projects around technology, and then consider users. All investments claim to “add value” to users, but they cannot offer in-context proof before doing the project. Social business changes all that because it can create and validate big data value propositions in context—before technology investments are made. This changes the rules. Here are some examples:

  • Big data team at outdoor/yard/patio retailer proposes project to mash up internal purchase, warranty, customer service and delivery data with external streaming data on sports schedules, weather, holidays, restaurant openings/closings and educational/racial demographics to boost sales/customer in select markets. Depending on the sophistication of their pre-existing analytics, this could be a long, costly undertaking. Use social business to identify, observe and interact with users, discovering how they use restaurants, demographics and outdoor home activities to build stronger friendships, families and careers (these are common emotional outcomes of entertaining).
  • Analytics team at commercial bank scopes an initiative to collect, analyze and deliver to management anonymized internal data from account openings, closings, ecommerce and mobile usage and customer penetration, combining with external streaming data from stock market performance, employment, self-employment and higher education performance. Use social business to validate highly desired customer and prospect goals and behaviors by identifying, observing and interacting with them. Then select mix of internal and external data to increase the bank’s ability to support users in reaching their goals.
  • Hightech components manufacturer and ecommerce firm wants to use internal and external data to inform website and mobile application design while supporting customers and prospects in social venues. It uses social business to develop high-trust relationships with passionate computer users like parents, photo studios, enterprise I.T. professionals and gamers. By observing users’ peer dynamics and interacting with users, the team learns what mix of internal and external data it needs to help users make their computers perform better, longer.

CSRA helps CDOs, CEOs and boards to use big data for transformation by using digital social analysis to create and validate understanding of markets and stakeholders. We use social, enterprise and third party data, develop strategy and test it by interacting with users. To learn more, see How We Work or contact me.

Big Data/Digital Transformation “Best of the Web”

Latest links from CSRA’s curated feed dedicated to using big data for digital transformation:

Useful map of #BigData vendor|technology|solution ecosystem - faint nod to #IoT & #wearable tech #kudos
MUSTread: Analyzes scenarios for converging mobility: vehicle, device, IoT; O/S business models, opportunities built on #trust Thx @jhagel
Deloitte/MIT research survey on #digital #transformation: using social mobile big data to change business
The new table stakes: Using software to get personal w #customers in #retail #cx
Rich coverage of #mobile #transformation trends: Practical insights: @forrester @johndeere @bosch @trunkclub & more
MUSTread adoption guide for enterprise #BigData & #Analytics
TCS.com #BigData study surprise: #SupplyChain & #logistics getting best ROI + culture change challenges

Even more links, the whole lot!

Big Data & Analytics Competency Center at the Chief Digital Office

Chief Digital Office Directory

  • Real-time presences & interactions:
  • Google+ (leaders) | Twitter (mainstream) | Home (concierge)

Big Data/Digital/Transform Reference

These are must-read resources for understanding big data & analytics as a transformation opportunity:

MUSTread adoption guide for enterprise #BigData & #Analytics
Four examples of #marketing collaborating w #finance, using #BigData & #analytics, to break silos, change rules, boost performance
How #BigData is rebadging 1970s "decision maths"; gentle debunk by former Mckinsey consultant suggests risks of overuse #kudos
Step-by-step how to use #BigData to outperform in marketing: ground initiatives in supporting customer outcomes of using your products
Case study: Analytics in #banking: KeyBank's head #analytics reports to CEO & leads marketing; he's CDO in all but title; #LessonsLearnt #kudos
DETAILED #BigData call to action for #CDOs: deep dive into how to develop capability #kudos
USEFUL #McKinsey research on global orgs' adoption of the digital transformation imperative

More reference/big data/foundation resources

Big Data/Digital/Transform Discussions

Join these conversations in which I’m participating about using big data for digital transformation:

[comment] TOUCHING, far-reaching holiday reflection on forgiveness and forgetting, from personal and institutional POVs #bigdata #fb
[commented]#CMO infographic tells a gripping story of the rare #marketing opportunity to improve ROI, featuring #McKinsey analysis #kudos
[comment] 4-step summary of lean #BigData approach #kudos
[comment] #BigData #healthcare example of the machine running amok - & how can we prevent it
[comment on why I'm optimistic] Debunking the #BigData hype, why it's doomed, warning signs
[comment] USEFUL viewpoint on how teams must change their approach & orientation to profit from #BigData
[comment] The untold #BigData story, driving enterprise agility & operations

More Big Data & Analytics discussions with a focus on digital transformation.

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