Introduction to Negotiation Strategy
At Oak Spring University, we provide corporate level professional Negotiation Strategy and other business case study solution. Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare case study is a Harvard Business School (HBR) case study written by Kiran R, Arunabha Mukhopadhyay, Dinesh Kumar Unnikrishnan. The Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare (referred as “Workstation Parag” from here on) case study provides evaluation & decision scenario in field of Sales & Marketing. It also touches upon business topics such as - negotiation strategy , negotiation framework, Customers.
Negotiation strategy solution for case study Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare ” provides a comprehensive framework to analyse all issues at hand and reach a unambiguous negotiated agreement. At Oak Spring University, we provide comprehensive negotiation strategies that have proven their worth both in the academic sphere and corporate world.
What’s my BATNA (Best Alternative To a Negotiated Agreement) – my walkaway option if the deal fails?
What are my most important interests, in ranked order?
What is the other side’s BATNA, and what are his interests?
VMW is a leader in software virtualization with approximately USD 6.5 billion annual revenue. VMW sells Workstation that can be bought online (store.vmware.com) and is used for running Mac on Windows. Workstation forms a significant portion of store revenues and most of it is bought online. There is rich digital/clickstream data for the visitors which can be combined with their past purchase history and other offline features as well. The business would like to increase sales of the product by targeting the right customers and needs a propensity model to be built using machine learning that can target the right set of customers. Michael Butler, the WW head of the store wants to leverage Parag's data sciences team to help him target the right workstation prospects that visit the store. A business conversation between Michael and Parag is followed by a technical discussion between Ravi, the data scientist and Parag. The following are the key questions that Ravi seeks to answer: -Cross-validation and evaluation in the context of huge imbalance in the data -Feature selection techniques -Communicating internal results such as lift curves back to the business -Different modeling approaches that can be followed -Interpreting the results for business decision making
By interests, we do not mean the preconceived demands or positions that you or the other party may have, but rather the underlying needs, aims, fears, and concerns that shape what you want. Negotiation is more than getting what you want. It is not winning at all cost. Number of times Win-Win is better option that outright winning or getting what you want.
Options are the solutions you generate that could meet your and your counterpart’s interests . Often people come to negotiations with very fixed ideas and things they want to achieve. This strategy leaves unexplored options which might be even better than the one that one party wanted to achieve. So always try to provide as many options as possible during the negotiation process . The best outcome should be out of many options rather than few options.
When soft bargainers meet hard bargainers there is always the danger of soft bargainers ceding more than what is necessary. To avoid this scenario you should always focus on legitimate standards or expectations, clearly understanding the arbitrage . Standards are often external and objective measures to assess the fairness such as rules and regulations, financial values & resources , market prices etc. If the negotiated agreement is going beyond the industry norms or established standards of fairness then it is prudent to get out of the negotiation.
Every negotiators going into the negotiations should always work out the “what if” scenario. The negotiating parties in the “Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare” has three to four plausible scenarios. The negotiating protagonist needs to have clear idea of – what will happen if the negotiations fail. To put it in the negotiating literature – BATNA - Best Alternative to a Negotiated Agreement. If the negotiated agreement is not better than BATNA (Negotiations options), then there is no point in accepting the negotiated solution.
One of the biggest problems in implementing the negotiated agreements in corporate world is – the ambiguity in the negotiated agreement. Sometimes the negotiated agreements are not realistic or various parties interpret the outcomes based on their understanding of the situation. It is critical to do negotiations as water tight as possible so that there is less scope for ambiguity.
Many negotiators make the mistake of focusing only on the substance of the negotiation (interests, options, standards, and so on). How you communicate about that substance, however, can make all the difference. The language you use and the way that you build understanding, jointly solve problems, and together determine the process of the negotiation with your counterpart make your negotiation more efficient, yield clear agreements that each party understands, and help you build better relationships.
Another critical factor in the success of your negotiation is how you manage your relationship with your counterpart and other people doing the mediation. According to “Kiran R, Arunabha Mukhopadhyay, Dinesh Kumar Unnikrishnan”, the protagonist may want to establish a new connection or repair a damaged one; in any case, you want to build a strong working relationship built on mutual respect, well-established trust, and a side-by-side problem- solving approach.
According to
Harvard Business Review
, there are three types of negotiators – Hard Bargainers, Soft Bargainers, and Principled Bargainers.
Hard Bargainers – These people see negotiations as an activity that they need to win. They are less focused less on the real objectives of the negotiations but more on winning. In the “Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare ”, do you think a hard bargaining strategy will deliver desired results? Hard bargainers are easy to negotiate with as they often have a very
predictable strategy
Soft Bargainers – These people are focused on relationship rather than hard outcomes of the negotiations. It doesn’t mean they are pushovers. These negotiators often scribe to long term relationship rather than immediate bargain.
Principled Bargainers – As explained in the seven elemental tools of negotiations above, these negotiators are more concern about the standards and norms of fairness. They often have inclusive approach to negotiations and like to work on numerous solutions that can improve the BATNA of both parties.
Open lines of communication between parties in the case study “Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare” can make for an effective negotiation strategy and will make it easier to negotiate with this party the next time as well.
Kiran R, Arunabha Mukhopadhyay, Dinesh Kumar Unnikrishnan (2018), "Machine Learning Algorithms to Drive CRM in the Online E-Commerce Site at VMWare Harvard Business Review Case Study. Published by HBR Publications.
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