Tom O’TooleClinical Professor of Marketing &Senior FellowKellogg School of Management

Putting Data Analytics Into Business Practice

So how do we really do this?

• Get started?

• Organize?

• Scale?

• Drive business outcomes?

There is a great surge of interest, initiatives and investment in big data and analytics

across a broad range of industries, categories and companies

Harvard Business Review October, 2012

IDC March 14, 2017

“…big data and business analytics solutions have finally hit mainstream…BDA as an enabler of decision support and decision automation is now firmly on the radar of top executives. This category of solutions is also one of the key pillars enabling digital transformation efforts across industries and business processes globally.”

The reality is that most companies are having difficulty figuring out how to really connect

data analytics to business outcomes

The success and sustainability of data analytics in practice will ultimately depend on producing

business results

How to put data analytics into business practice?

How to connect data analytics to the business?

In legacy businesses?

• Industry/business structure (e.g., franchisees, dealers)

• Multi-channel (e.g., brick and mortar, direct sales, channel partners, digital)

• Established organizational structures (i.e., business units, functions)

• Incumbent talent and work force

• Multiple IT systems developed at different times for different purposes

It’s More Difficult In Legacy Businesses

Most companies are legacy businesses

In February, 2015, the CEO said…“I’d like you to develop an enterprise analytics function for us.”

“I think that this could be a competitive advantage and create a lot of business value.”

“If you need to hire the smartest person from Amazon, go do it.”

1.Define terms, scope, business objectives, time frame and expected outcomes

2.Educate the C-level and senior executive team

3.Learn from other companies’ experience

4.Be inclusive of all functions potentially involved

5.Assess current state, uses and maturity level

6.Identify priority use cases (i.e., specific business problems)

7.Specify enabling requirements and get initial commitmentA. Functional staff (multiple roles - data scientists, translators,…)B. IT development and systemsC. Short-term investment

8.Deliver short-term wins that produce business value and/or practical utility

9.Develop multi-year roadmap to scale up organization, scope and investment

Approach

• Focusing on technical expertise, tools and techniques

• Lack of agreement on definitions, scope, time frame and expected outcomes

• Lack of senior leadership advocacy and involvement

• Lack of organizational integration with the business

• Underestimating IT requirements

Typical Ways That Analytics Initiatives Fail

Definitions and Scope

Definitions• “Big data”• “Analytics”• “Advanced analytics”

Scope• Enterprise• Priority functions• Customers

Time Frame and Expected Outcomes

Time Frame• Short-term (e.g., 90-day) • Same year• Multi-year

Expected Outcomes• Revenue lift• ROI• Other (e.g., share gain)

Three Required Sets of Capabilities▪ Strategic thinking▪ Problem definition▪ Interpretation▪ Implementation

▪ System architecture▪ Software platform▪ Systems integration▪ Data provision

Business

Technology Analytics▪ Data science▪ Analytics plan▪ Model building▪ Visualization

DataAnalytics

Leadership

Technology

Each type of capability includes multiple different roles

Organization and Functional Structure• A set of types of roles is required

• Data scientist• Data steward• Model builder• Business analyst• Technology architect

• There is no one right answer for how to organize the analytics function• Organizational structure and C-level reporting• Decentralized, centralized or hub and spoke model• Center of Excellence• Must work for the business structure, processes, requirements and culture

• Create a culture of intellectual curiosity

• Encourage, enable and expect people to:• Ask “How could we use data to…

• Answer that?”• Predict that?”• Optimize that?”

• Share data

• Create an evidence-based culture

Culture is most important

“Culture is the key ingredient to ensuring data investments achieve their potential…How does one change a company’s culture to become more data-driven? It all starts with curiosity.”

Winning With Data. Tunguz and Bien. 2016

• The analytics function in practice is wholely dependent on information systems (i.e., on the IT function)

• Without the commitment of top IT leadership, dedicated IT resources, IT development prioritization and required IT investment, the data analytics function will at best be hobbled and will likely fail

• The relationship between the analytics function and the IT function is a likely fault line that needs to be explicitly addressed

Analytics Depends On IT

Most companies underestimate the IT requirements and the need for IT commitment

• Solve practical business problems

• Create business value

Focus on Using Data Analytics To…

1. Let business use cases drive the analytics

2. Optimize

Guiding Practices For Success

• Predict and reduce “no shows” (medical imaging clinics)• Predict and avoid compliance violations (financial brokerage)• Predict and avoid misconnects and lost bags (airline)• Target ancillary products/services for revenue lift• Predict and reduce high value customer attrition• Allocate digital marketing investment for greater effectiveness

Use Data Analytics To Solve Practical Business Problems

• Targeting• Messaging• Product• Displays• Configurations• Combinations• Pricing• Offers• …

Optimize• Test and Learn• Dynamically• At Scale

Example 1

How to increase food sales?

Example 2

How to increase basket size?

Stages In The Data-Business Relationship

Using data to manage the business more effectively and efficiently

Using data to change how the business is managed

Developing a new business model based on data enablement

It’s Like Getting HealthyYou can either:Develop the right mindsetLearn the fundamentalsDevelop a sound initial regimenActually start working outProduce evident results that you like and others seeExpand and intensify your physical training programCompete at a high level

Or you can:Buy the latest equipmentTalk a lot about what you’re going to doFall short of your expectations