In foreign affairs and national defense, especially among academics, it has becoming more common to talk about grand strategies. There is a very popular course at Yale University by John Lewis Gaddis called On Grand Strategy, and in 2018 he published a book worth reading with the same name.
An emerging definition for grand strategy for state is “something that has the characteristics of being long-term in scope, related to the state’s highest priorities, and concerned with all spheres of statecraft (military, diplomatic, and economic) [Silove 2018].” Of course, the problem is that a strategy in general is concerned with the long term decisions that an organization makes to further its priorities, so this definition doesn’t help as much as you might hope. See the Appendix for a definition of analytic strategy.
There is though some common themes that emerge if you review some of the recent articles on grand strategies [Biddle 2015, Silove 2018; Gaddis 2018]:
- Grand strategies are longer term than typical organizational strategies, for example, 20 or more years. Fifty and hundred strategies are not unusual in China.
- Grand strategies cover more domains than typical organizational strategies. For example, grand strategies for states typically cover military, diplomatic and economic strategies, and not just one of these.
At the Other Extreme – A Lean Analytic Strategy
Before discussing grand analytic strategies, it is probably helpful to start at the other extreme (see Figure 1) and briefly mention lean analytic strategies. In the post, I discuss developing a lean analytic strategy and introduced a lean analytic canvas modeled after the business model canvas for lean start-ups. For start-ups, smaller companies, and smaller units in larger organizations, the focus should be on developing an end to end system with analytics that some value as soon as possible, and iteratively improving it to increase the business value that it delivers. A lean analytic strategy is a good way to do this. You can find more information in Chapter 10 of my book: Developing an AI Strategy: A Primer and a definition of a lean analytic strategy in the Appendix of this post.
Five Questions for a Grand Analytic Strategy
At the other extreme, for larger organizations with multiple divisions and planning that extends out five years or more, it may be appropriate to consider developing a grand strategy for analytics that includes answering questions like the following?
- In the long run, how much of the IT, data and analytic ecosystem do we buy vs build? What new technologies should we develop to advance our strategy in analytics?
- What are our long terms alliances and partnerships in analytics?
- How can we develop, promote and influence standards in analytics to support our strategy in analytics?
- How can we best leverage lobbying and influence legislation to support our long term strategy in analytics?
- How can we educate our users in particular and the public more generally so that they understand and support how we use data and analytics in our products and services, while balancing privacy with improved functionality?
An Example – Google’s Grand Strategy in Analytics
Alphabet’s revenues for 2019 were over $161 billion and leveraged their analytics and AI to drive revenue across the various subsidiaries of Alphabet and and divisions of Google and leverages advances resulting from investments in fundamental computing and analytics over years. The second paragraph of Alphabet’s fourth quarter 2019 earnings release [Alphabet 2020] reads:
Our investments in deep computer science, including artificial intelligence, ambient computing and cloud computing, provide a strong base for continued growth and new opportunities across Alphabet.
Source: Alphabet 2020.
A recent report from CBInsights writes:
[Google] is also seeking out new streams of revenue in sectors with large addressable markets, namely on the enterprise side with cloud computing and services. Furthermore, it’s looking at industries ripe for disruption, such as transportation, logistics, and healthcare. Unifying Alphabet’s approach across initiatives is its expertise in AI and machine learning, which the company believes will help it become an all-encompassing service for both consumers and enterprises.
Source: CBInsights, Google Strategy Teardown, 2020.
From Lean to Grand Analytic Strategies
To summarize, as Figure 1 shows, there is a spectrum of analytic strategies, as the complexity of the organization grows and as the time frame of interest lengthens. As you move from left to right in the figure, the scope of the strategy becomes broader and broader.
A lean analytic strategy is a shorter term strategy for an analytic start-up or a smaller unit within a large organization, and is concerned with the core of any analytic strategy: how data is collected or generated; how data is transformed using analytics to produce scores or other outputs; how the outputs are used to create something that can be monetized or something that otherwise brings value to the business; and how this whole chain can be protected from a competitive standpoint.
An analytic strategy specifies the long-term decisions an organization makes about how it uses its data to take actions that satisfy its organizational vision and mission; specifically, the selection of analytic opportunities by an organization and the integration of its analytic operations, analytic infrastructure, and analytic models to achieve its mission and vision.
A corporate analytic strategy is an analytic strategy for two or more strategic business units, and it includes a plan for allocating resources across the business units.
A grand analytic strategy is longer term in scope than a typical analytic strategy and is designed for large complex organizations with various subsidiaries, divisions, or strategic business units. A grand analytic strategy is concerned with all spheres and interactions of the organization with analytics, both internal and external, including the broader technological landscape, regulatory and legal landscape, public perceptions, societal trends, etc. around analytics and its applications.
For more information, see: Developing an AI Strategy: A Primer.
References
[Alphabet 2020] Alphabet Announces Fourth Quarter and Fiscal Year 2019 Results, retrieved from https://abc.xyz/investor/static/pdf/2019Q4_alphabet_earnings_release.pdf, on November 1, 2020.
[Biddle 2015] Tami Davis Biddle, Strategy and grand strategy: What students and practitioners need to know. Army War College-Strategic Studies Institute, Carlisle, United States; 2015 Dec 1.
[CBInsights 2020] CBInsights, Google Strategy Teardown, 2020.
[Gaddis 2019] John Lewis Gaddis. On grand strategy. Penguin Books, 2019.
[Silove 2018] Nina Silove, Beyond the Buzzword: The Three Meanings of “Grand Strategy”, Security Studies, 27:1, 27-57, 2018, DOI: 10.1080/09636412.2017.1360073
Notes About Links
There are no affiliate links in this post and I get no revenue from the Amazon links. I do get a royalty from the sale of the book Developing an AI Strategy: A Primer.