Joseph Napolitan, who worked on the presidential campaigns of former US Presidents John F Kennedy and Lyndon Johnson, and also orchestrated Vice President Hubert Humphrey’s dramatic rise in 1968, was credited with coining the term “political consultant”.

In his 1972 book, The Election Game and How to Win It, Napolitan employed a well-worn analogy – that is, election campaigns are games, contested with certain rules and require the formulation and execution of successful game plans. Napolitan even described how he took advantage of electronic campaigning and political polling.

The dynamics of the game of political consulting might have been dramatically redefined in today’s era of the internet, social media and big data and with the infiltration of Moneyball culture. The 2003 book Moneyball by Michael Lewis – and 2011 movie starring Brad Pitt – tells the real story of how the Oakland Athletics’ manager Billy Beane used analytics to achieve success in Major League Baseball despite a lean budget.

In the 2008 American presidential primaries, Barack Obama defeated Hillary Clinton to win the Democratic nomination and then Republican candidate John McCain in the race to the White House. Political experts attributed a significant part of Obama’s success to big data analytics.

Volunteers canvassing for Democratic gubernatorial candidate Beto O'Rourke on in Austin, Texas, on November 7. Credit: Reuters.

The Obama campaign put every potential voter into its database, along with hundreds of tidbits of personal information. The data-driven model allowed the campaign to micro-target individuals through email, snail mail, personal visits, and television ads seeking donations and votes.

Four years later, Republican nominee Mitt Romney again lost ground to Obama in terms of big data analytics – the Obama camp had, in fact, run a national campaign like a local ward election, where the interests of individual voters were known and addressed. Elections everywhere would soon be affiliated with the slicing and dicing of big data, inevitably.

In 2016, Hillary Clinton made another run at the presidency. The software programme Ada used by her campaign, however, failed to capitalise on data. Big data is certainly not a panacea – with all the major contesting campaigns now using data analytics, it cannot be so.

In today’s world, any political party using data scientists to frame their strategy is not news anymore – rather, it would be a surprise if a professional team does not have a formidable data science department.

What about India?

Political strategy and consulting firms have mushroomed across India. So, how important are these political consultants in today’s politics and society? Apparently, very much so.

They conduct several on-ground surveys to understand the concerns of the voters and also use data mining and statistical analyses to frame strategies – using the poll-booth data of each constituency and historical data on a shift in voting patterns. The quality of the statistical frameworks of these surveys and the resulting data may certainly vary, and often, is unknown.

The important question is: can a political strategist really provide the Midas touch, always? Not really. Even Prashant Kishor, possibly India’s most-high-profile political strategist in recent times, witnessed a disastrous failure when he worked for the Congress in the 2017 Uttar Pradesh assembly elections.
India votes on the basis of caste, creed, religion, local and regional factors, and, of course, the charisma of some leaders. There is no common template in this complex society and every constituency depicts a separate story.

Election strategist Prashant Kishor. Credit: Reuters.

My personal conviction is that most – perhaps not all – statistical analyses by election strategists are routine exercises that may often end up preparing several charts and diagrams and extracting basic statistical features, with a focus on micro-targeting.

In his 2019 book How to Win an Indian Election, Shivam Shankar Singh, who worked with Kishor’s Indian Political Action Committee, or I-PAC, observed that creating graphics and organising events provide a different ambience to the election.

There is no denying that social media is an effective instrument in election strategies today. However, the information contained within that data is so vast, that most political strategists might fail to analyse it in an optimal statistical manner to extract something that may offer a hidden opportunity.

A data analysis-based strategy may enhance a few percentage points of the vote share if the opponent does not have a formidable data science team. But today, with every major political party depending on data science and political strategists, even Hillary Clinton or her rival must face defeat. Is it then partly a tussle between the expertise of the two groups of data scientists?

Again, I am inclined to believe that many key strategies in most elections are shaped by wisdom and consequent efficient management. Data plays a less important role, and “efficient” data analysis, even lesser.

Pushing successful winning slogans – “Punjab da Captain” for former Chief Minister Amarinder Singh’s campaign in 2017, or “Bengal wants its own daughter” in 2021 for Chief Minister Mamata Bengal’s campaign – or capitalising on a slip-up or comment by any opposition leader are signs of smart political instincts. Still, in today’s Moneyball era, statistics is the third eye, and big data and data science are here to stay – in our lifestyle and politics.

Can political strategists really “sell” the candidates or political parties to the voter-consumers? To some extent, maybe. Napolitan, however, believed that the whole idea of “selling” candidates is a misnomer. He thought that candidates who win are those whose personalities and approaches to issues make for “instant involvement” with viewers and listeners. Well, to exhibit magic, you may possibly need a Narendra Modi, a Mamata Banerjee, or an MK Stalin to make strategies for, especially in a favourable political ambience.

Atanu Biswas is a Professor of Statistics at the Indian Statistical Institute, Kolkata.