The Value of Data in Digital-based Business Models: Measurement and Economic Policy Implications

The Value of Data in Digital-based Business Models: Measurement and Economic Policy Implications Carol Corrado Jonathan Haskel Massimiliano Iommi Cecilia Jona-Lasinio

OECD Workshop The Value of Data to Consumers June 3, 2021

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Data and digital-based platforms

 Digital transformation is affecting whole societies, and is a topic of interest in many disciplines  In a digitizing economy, many economic activities are potentially driven by data.  Data are becoming a key corporate asset, complemented with analytics, and organizations are  Investing heavily in digital platforms and data analysis  Demanding a workforce with skills in data science

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Questions addressed in forthcoming report for the OECD

 Does the increase in business use of data have first-order impacts for the conduct of economic policy?  Is digitized information (i.e., data) driving industrial innovation? Improving consumer welfare?  Is data appropriately accounted for in GDP and CPI statistics?  Is data affecting the workings of the macroeconomy, i.e., business pricing, response to demand shocks?  What are directions for future research?

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Approach: Data as an Asset and Main Policy Challenges

Data as an asset

New products and increased variety

Consumers

Firms

Increased efficiency gains

Data markets

Macroeconomic policy Monetary and fiscal policies

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Structural policy Competition policy Data policy

International trade policy International standards

Discussion topics: • • •

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Approaches to the analysis of data  Data as an asset Consumer data markets and policy Conclusions and implications

Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Approaches to the analysis of data

 Data usually refers to “big data”  We make the case for treating data and the knowledge gained from data analytics as a longlived asset  Implies that firms invest to create data assets of value  Implies that asset provides services that contribute to production in an economy

 Data assets are nonrival (though excludable) goods  The market for data and economic policy around data needs to be analyzed with reference to its nonrivalry and excludability

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Distinguish types of data according to ”work done” to store, process, and analyze data for input to decision-making

Data as an asset

 Capital formation requires investment activity  Economic approach to “data stack” referred to in business  Three types of data assets (table)

DATA AS AN ASSET: INVESTMENT ACTIVITIES AND ASSETS PRODUCED

 Intangible investment (full expanded framework) includes  Most data assets and  Data tools and data analytics apps

Asset Type

Comments

(1)

(2)

(3)

1

Generation and collection

Data stores (“raw” data)

Experiments and platforms that create and/or collect data

2

Curation and aggregation

Databases (query-ready)

Processes and platforms for combining and curating data from multiple sources

3

Analysis/Analytics

Data intelligence (actionable)

Gleaning of insights from data that can be acted upon

 Data monetization occurs

 Once actions are implemented  Requires co-investments in other intangibles (and tangibles)

Activity

“Data Stack” 7

Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Intangible investment  Business intangible investment is long-lived spending on:  Software and databases

•

 R&D

•

 Entertainment originals  Design and other new product development (e.g., new financial products)  Brand and customer development  Enhanced organizational practices (e.g., supply chains, worker training)

 Business intangible capital is the stock of commercially valuable knowledge (whether science-based or not).  i.e., “blueprints” and business models

 Intangible investment framework applies to public and nonmarket sectors

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

•

All categories involve data and data analysis Aligned with Statistics Canada Data framework Increased data intensity has created efficiencies in intangible investments, e.g., marketing and training

Discussion topics: • • •

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Approaches to the analysis of data  Data as an asset Consumer data markets and policy Conclusions and implications

Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Consumer attitudes about data practices: Surveys suggest that data security, third-party sharing, and lack of transparency are consumers’ top worries

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Perspectives on data  Active Data Policies Include:

Business information potentially covers more than personal information

 EU: General Data Protection Regulation (GDPR)  US: California Consumer Privacy Act (CCPA)

Welfareenhancing growth Economic policy perspective - Data as personal

Business perspective - Data as business information - Data as an intangible asset

information - Data as a nonrival good

Privacy concerns (consumers) To what degree should personal information be exclusively held?

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

 Australia: Consumer Data Right (CDR) targeted to the banking sector.  GDPR and CCPA both cover large markets and have extraterritorial effects, as they cover businesses incorporated beyond their respective jurisdictions  GDPR’s provisions are stricter than CCPA  These policies attempt to guard against unwanted third-party sales

Data markets: Consumers trade in their data

Consumer supplies data

…….

to firm who builds asset

 About 40 percent of global consumers are willing to be tracked in exchange for discounts, services, or locational information

Data supply Consumer

 Consumers’ value free content significantly more than personalized content as a benefit of sharing data

Firm

Reward

(implicit or explicit)

 Discounts on car and health insurance are among the most convincing benefits

 Consumers are differentiated across countries regarding desires for oversight (government vs private watch dog) and ownership/control  Likely some endogeneity (Europeans favor government watch dog)  Though consumers clearly see value in their data, not clear they appreciate benefits to data “sharing” across organizations (i.e., the nonrivalry of data)

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Competition and privacy policy  Competition policy often framed in terms of a “digital market”  Digitization ≠ the market (i.e., data markets are where data trades occur)  Data (“raw” data) as a by-product of a transaction. Is that a trade?  Policy depends on consequences of data trades – Assets can be traded (e.g. I give my data to Google and get search engine services). Are there market failures in these trades?

Rate of return, 1999 to 2016 US market sector industries .20

.20 Without Intangibles

 Digitized raw data becomes codified knowledge (“data stack”)  Firms with high data investment rates may seem to have high profits or markups but intangible assets (which include most data assets) are usually excluded from these calculations.

 Cross-cutting issue: privacy  Privacy = total excludability. Privacy as a “right”/”merit good” = prohibit market altogether?  …versus leaving consumers to acquire security (VPN, ad blockers) and encourage corporate transparency 13

Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

With Intangibles .05

.05

Note: After tax ex post nominal rate.

Discussion topics: • • •

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Approaches to the analysis of data  Data as an asset Consumer data markets and policy Conclusions and implications

Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Conclusions and implications

 Consumers’ main concerns about business use of their data are security, third-party sharing, and lack of transparency.  Businesses need to up their game to address these concerns (and policy needs to encourage disclosure in corporate reports and promote cyber security)  Key policies (esp. GDPR) address third-party sharing, though studies reveal some unintended consequences  Policies need to be analyzed in context of actual/evolving data markets and have clear objectives – Policies that best address sharing and privacy of biodata and personal health records across institutions and geographies do not necessarily apply to marketing data on consumers, etc.

– Competition policy needs to refer to market imperfections, account for existing market mechanisms (e.g., VPNs), and recognize the value of the intangible assets driving firm profits and returns.

 Our full report on “The Value of Data” will include additional analysis of the macroeconomic, productivity, and measurement challenges to increased data use.

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017

Thank you.

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Carol Corrado, The Outlook for the US Economy, Brookings, www.conferenceboard.org Mary 31, 2017