Most companies started 2020 with a plan. By January 20, that plan was becoming obsolete, and by January 31, it was history. The world’s economic landscape seemed to change overnight, and businesses were struggling. Organizations needed different business plans to navigate the COVID-19 landscape, but this was uncharted territory.
Corporations have disaster recovery or business continuity plans. These plans address natural disasters or service interruptions such as a down power grid or security breach. But, who has a plan for surviving a pandemic? Organizations that were around during the H5N1or avian flu scare may have a pandemic planning document in some dusty corner. But for most businesses, there is no template.
Agile Companies
The current business environment will be a true test of the agile methodology. Agile organizations work collaboratively to release products and services as quickly as possible. By streamlining their processes, they can adapt quickly to address a changing market landscape. No matter how agile a company is, it is the decisions that are made during this pandemic that will determine a business’s future.
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React or Respond
Businesses like people react or respond to situations, but what does that mean in a worldwide crisis? Companies react in-the-moment from a sense of survival. The reaction may not be immediate, but it will be subjective, based on inarticulated assumptions or biases. A response is based on information. Although assumptions and biases do factor into a reply, businesses that respond consider the long-term effects of a decision. In most cases, a response is not immediate.
In business, reactions are viewed negatively because they fail to take into account the long-term ramifications. Responses are seen as more measured because they are based on data that looks at long-term consequences. What if an organization could react quickly with a data-driven response?
Data-Driven
Two factors differentiate reactions from responses: time and data. The assumption is that a quick response must be reactionary because data is not immediately available. With today’s technology, that assumption is no longer valid. If a company has embraced the concept of digital transformation, they have incorporated data collecting methods from across their enterprise.
With appropriate data analytic tools, organizations can aggregate data from multiple sources to reveal a more comprehensive assessment of potential impacts. Let’s take a simple example.
A financial institution has a physical and virtual presence. Suddenly, the physical option is removed. Can the company’s virtual services meet customer needs?
Conventional Wisdom
Conventional wisdom would say that people over the age of 65 would use in-person options with a small percentage using virtual options. It would also suggest that younger customers are already using virtual services. Using this “wisdom,” a financial institution might decide to focus resources on helping seniors.
Data-Driven Decisions
With data, a financial institution might realize that:
- 75% to 80% of customers under the age of 45 primarily use virtual services.
- 65% of customers over the age of 45 primarily use virtual services.
Although older customers do prefer in-person services, it is not just those over the age of 65. Dedicating resources to only seniors misses one of the most profitable market segments — ages 45 to 65. In addition, the organization’s data found that customers between the ages of 30 and 44 do not use remote deposit capture, which poses a problem if customers are stuck at home. Suddenly, an institution can personalize its customer support.
Every business is struggling to make the best decisions possible without risking its long-term viability. The best decisions are informed decisions that come from data. In today’s environment, a business will have to move quickly to adapt to the changing landscape. At the same time, companies need to make decisions for the long term. Let us help you find a data strategy for now and into the future.
- Data and the Post-Pandemic World - June 30, 2020
- Data-Driven Decision Making in Recessions - June 16, 2020
- What You Need To Know About Data Driven Decision Making - May 26, 2020