Many good articles are already written covering Bihar election in detail, however I am trying to see the verdict with my data spectacle. I have mined Bihar election verdict with respect to data, I have avoided concluding anything based on subjective argument or argument based on perception,purpose of this exercise is to understand how voter’s sentiment affect election outcome, also why managing voter’ sentiment is most crucial task in election.
My argument is based on data insights, henceforth many probabilistic scenario which actually affected Bihar voters mood is discussed at length,many points highlighted here can be classified as subjective point but I would like to present data insights as much as possible for facilitating my point of argument.
To start with, I would like to bring 2014 Loksabha election as one of our focal point for discussion, NDA won 31 seats and Mahagathbandhan won 9 seats,however if we go deep into data few interesting data facts emerged out which in-fact affected 2015 Vidhansabha election as well, but at this point I would not be drawing any conclusion. Let’s see the 2014 Loksabha data in detail :
2014 Loksabha election result data was highlighting few interesting data facts, let’s understand pattern in depth , Mahagathbandhan took a lead in 146 Vidhansabha seats while NDA took a lead in 97 Vidhansabha seats in Loksabha election, one way I can reach on direct conclusion saying if JD(U) fought along with RJD+CONGRESS combine then in Loksabha 2014 result in Bihar would have been different , but this conclusion is not entirely true, Loksabha election had been fought on “agenda for change” , and there was a strong wave in favor of Modi henceforth directly adding voting percentages won’t yield correct result, however a possible hint can be definitely be drawn.
After 2014 Loksabha election , many things on ground had been changed ,Nitish and Laloo realized the benefits of staying united with Congress, this had immediately gave them political benefit in By-Election held in August 2014 when they won 6 out of 10 seats , NDA managed to get 4 seats only, writing on wall was giving a interesting data insight “Mahagathbandhan voters are vocal & aggressive as well as numerically their strength is more” Basic idea of till this point , combined Nitish Laloo and Congress (although it had very limited role to play) had formulated stronger caste arithmetic on ground and their strength was visible on paper .
With backdrop of above analysis, using socio-economic data, historical voting pattern, opinion polls and collecting data throughout election period following scenarios are emerging out defining why NDA lost the election.
- Favorable caste arithmetic for Mahagathbandhan
- Statement on reservation, thereafter failure of local NDA leadership in countering Mahagathbandhan’s argument on reservation (Merit of statement is subjective)
- Mistakes in candidate selection , problem of “rebel candidate”
- NDA failed to measure possible impact of food inflation issue specially “Arhar Daal” issue
- Failure of NDA partners in mobilizing/transferring votes to other NDA partners
Infighting between alliance partners(HAM(S) vs LJP) for dalit leadership
- Failure of local NDA leaders in mobilizing backward class votes in their favor
- Failure of top BJP leadership in controlling alliance partners and their demands
- Missing of real time public sentiment data– failed to gauge public mood after big ticket events/statements for NDA
Let’s start with Mahagathbandhan favorable caste arithmetic, Laloo started his campaign with a rally as well as Bihar bandh for publication of caste based census data , initial response from public was not very exciting ,however a remark on reservation gave him a burning ball , merit of remark is subjective but timing of remark as well as failure of local NDA leaders to counter Laloo’s argument on reservation gave Mahagathbandhan a plus in campaign against NDA. Local leadership of NDA was seen totally helpless in countering Laloo’s assault over reservation remark, election had been changed from package based politics to caste based politics.Mahagathbandhan favorable caste combination has strong presence in 181 seats , and Mahagathbandhan won 133 seats and NDA won 44 seats out of 181 seats.
Failure of NDA partners
Failure of HAM(S) in transferring votes to NDA candidates specially to LJP candidates , Our analysis suggest HAM(S) was very effective in 14 seats, and they had balancing power in 37 other seats of Bihar Vidhansabha seats,but they failed to muster support from their supporters and performed miserably.
Failure of LJP – LJP contested 42 seats and won just 2 seats, ticket distribution was major reason for LJP’s failure – classic case is Bochahan, Kalyanpur, Raja Pakar seats, list is long and political leadership should introspect this.
Failure of RLSP -RLSP contested 23 seats and won just 2 seats, supports from “Kushwaha” community was very crucial during Loksabha-2014 election but in vidhansabha election Upendra Kushwaha could not manage to get big support.
Real time voter’s sentiment analysis was a missed element in NDA campaign
Bihar election was unique in nature where many national events/incidents were happening simultaneously which directly or indirectly impacted voters mindset, capturing voters mood on real time basis is very important for deciding campaign strategy, local leadership reactions on many subject came later than expected.
Ticket distribution issue was another major reason for NDA failure, Mahagathbandhan also faced problem after ticket distribution but leaders from Mahagathbandhan managed it in early stage of election ,in NDA ticket distribution issue stretched till last, rebel party candidates impacted many possible winning seats. It is also important to note that rebel candidate just not impact concerned seat but they also impact neighboring seats, a complete collateral damage.
Bihar election has many lessons for political parties they should seriously take “Information advantage is key for success” theme , election strategy should be formulated around public mood and should be flexible to adjust on real time data.
Author : Basant Kumar
Disclaimer: The opinions expressed within this article are the personal opinions of the author. The facts and opinions appearing in the article do not reflect the views of Datamineria and Datamineria does not assume any responsibility or liability for the same.