Numbers are never perfect, but they can determine business size quantitatively. Data can be very helpful as a referee in stakeholder negotiations and decision-making by making quantitative trade-offs.
“For example, changing the sentence ‘higher spending to get better opportunities’ to ’20 percent higher spending, but only 5 percent better experience and 5 percent retention, translated to 10 percent CLV’,” said Aussie Hayono, BA, MA, the Director of the Marketplace Grab Indonesia, in his session as a guest lecturer at the MBA SBM ITB Jakarta, Tuesday (6/7/2021).
Aussie believes that data helps internal (business function) and external (public relations, customers, and suppliers) stakeholders in decision-making. Therefore, the analytical team/consultant often acts as a third-party referee/negotiator to achieve a win-win solution across the company.
In his presentation, Aussie gave several references to establish and improve a company, one of which was Masters of Scale by Reid Hoffman. “If you want your company to really thrive, you have to first do things that aren’t growing,” the Aussie quoted him as saying.
Build the core experience by hand, serve your customers one at a time, then figure out how and what to improve. “And, if you’re not shy about launching your first product, you’ve launched it too late,” he added. According to Reid in his book, imperfection is perfection, because assumptions about the customers’ desires are never true. Instead, from these imperfections, business people learn to be perfect, and of course, those imperfections will not damage the company.
Aussie also provides some examples of data analysis methods and their respective characteristics. Among them is Explanatory Analytics, a method that makes context and business acumen paramount. This method can improve the visualization of SQL and python data, has an exploratory nature and connects the points that are not well connected. In addition, Aussie also explained about Statistical Modeling for moderate business contexts, as well as ML Engineer/Algorithmic Products focusing on releasing algorithmic products.
