By Haider Nazar
A company’s reputation is one of its most valuable assets. However, reputational risk is rarely quantified or connected to financial performance. Reputation management teams instinctively understand the importance of protecting and maintaining their company’s reputation. And they’re also keenly aware of the potential negative impacts of not actively managing and monitoring their reputation. However, the very discipline dedicated to this work – reputation management – has its challenges – mainly due to its outdated approach.
Historically, corporate reputation has been measured using sentiment analysis. This approach – using surveys, polls and media metrics – provides reputation teams with a fraction of what’s needed to effectively manage their company’s reputation. Additionally, another problem with this approach is that it creates a ‘perception-only’ framework for analysis. Current reputation management solutions that rely exclusively on sentiment data are limited because they do not take into account facts linked to corporate behavior; they require constant polling, which is a slow and expensive process, and they rank without providing deep insights on how to improve. They also provide insight on limited data (such as good pay, flexible hours) as well as do a poor job of predicting future reputational risk.
A Reputation Intelligence Solution
Imagine if your company could effectively leverage AI to quantify financial risk and build more trust with key stakeholders. As companies are all looking for better ways to reach and influence those who matter most, the reality is that persuasion rarely works, instead, a much more powerful approach is to lead with facts followed by action. That’s where MAHA Global’s Darwin steps in – the first reputation intelligence platform which unifies multi-stakeholder sentiment, corporate behavior as well as competitive and financial analytics. Darwin makes it easier for management teams to see in real-time how their actions on environmental, human capital, social impact and enterprise risks compare to their competition, while isolating the reputational attributes that impact performance and drive the greatest financial risk.
How Does Darwin Do It?
While outdated approaches capture just a fraction of what management teams need to know to effectively manage their reputation, Darwin helps pinpoint, predict and take action on your company’s reputation, ESG and business risks. The power of Darwin’s analytical method comes from the pairing of newly available big data with a deep bioscience intelligence engineered by Dartmouth scientists who are using the same mathematical models to isolate attributes among species that lead to survival, adaptation and extinction. For the first time, these methods can be applied to corporate data sets.
Practical Applications
By starting with behavioral data and learning what is relevant to reputation, MAHA can generate data that goes beyond what people think, feel and say and instead, provide an on-demand, forward-looking analytical tool to inform what companies need to do. With real-time clarity, our reputational intelligence platform can help guide your team, C-Suite and board of directors, providing forward-looking analysis grounded in financial models, AI and science – providing reputation teams with a scientifically oriented research product to bring into their boardroom. Additionally, you can more effectively prepare for your earning calls. You can also build more trust with your workforce (e.g., when working through labor relations issues). Furthermore, if you’re handling a M&A transaction, our predictive analysis can help you better understand the reputational risks associated with the company you’re acquiring.
In the end, the decisions on what to support and when to speak publicly, stay silent and take an appropriate action are just not getting any easier. In an increasingly complex and data driven market, companies need real-time, data-driven, predictive solutions, with the most accurate insights into what is helping and hurting your reputation, what people think/say about your company, how action/inactions influence your brand’s reputational risk, how that risk is linked to financial performance and what your competitors are doing that you are not (but should be).
