Data-Driven Culture, Digital transformation is taking place in a lot of companies these days. As more processes are digitalized, more companies recognize the potential for Artificial Intelligence-driven efficiency improvements. However, increased AI use is not without obstacles usually found in the structure of an organization’s workflow.
Even though digitization and automation are becoming commonplace across industries, many companies still need a one-to-one data-driven culture. A data-driven culture involves more than analyzing the trends in the BI platform and running scenarios. It’s an attitude that allows companies to adapt to their customer’s needs and utilizes data to justify their decisions.
Companies can only establish data-driven practices slowly, but now is the perfect moment to begin. As AI use grows and so will the data volumes that have caused massive data-driven analytics becoming more crucial than ever before. Therefore, companies must shift away from a “gut feel” approach to decision-making in favor of a data-driven decision-making framework.
Prioritizing the most critical business tasks adoption has brought attention to data quality. Companies have been collecting customer data for years and have paid little to the accuracy and reliability of the data. AI algorithms trained on low-quality data can lead to less-than-optimal results for the business.
An investigative piece published by The Markup in 2021 detailed instances of mortgage underwriting algorithms denying minority loan applicants much more frequently due to past biases in data used to train. Inaccurately gathered data can lead to such results and create negative perceptions of brand image, which financial institutions require less.
Analyzing the sources of data can be the initial step to finding potential landmines, such as the example in the previous paragraph. The company must look over the information they’re collecting and the information they’re removing. Teams often throw out irrelevant data to their processes; however, those data sets could be helpful in other processes.
Furthermore, data identified as “noise” typically provide valuable information that can give AI algorithms context. Some noises could be more helpful. Data-driven companies know the variables that have a significant role in their operations and categorize data.
Data collection and analysis is, therefore, a centralized job. Although individual units may contain data scientists within their respective units, a central data team needs to establish policies and schemas. Without this central view, companies will be blind to their vision which can lead to poor results that hurt their businesses.
If a company takes the first steps in dissolving all of its information, the ideal first step is to look at the most critical operations. In most cases, infrastructure needs some overhaul too. The ability to link technology investments to top-level business goals can help secure support and propel companies toward data-driven growth more quickly.
In the end, technology like AI is an instrument but not an answer. It’s only as good, depending on the information it gets.
- Pilot projects that have demonstrable results
Despite the immense focus AI and ML-based algorithms have received in recent times, only a tiny percentage of businesses can trust these algorithms. A 2021 study conducted by New Vantage Partners highlighted that only 12.1 percent of the companies that were who were surveyed used AI widely in production. The remainder were either unsatisfied with AI (thanks to the erroneous results) or were hesitant about expanding the use of AI.
Change is a lengthy time in the business. But technology has altered our notion about what “long” means. Since innovation has accelerated in the past decade, companies can’t afford to remain in the shadows and not consider the potential AI or a data-driven approach offer their companies.
Securing the approval of executives is a significant obstacle to overcome. Although most executives can’t be accused of being ignorant of the benefits of AI but gaining their approval depends on convincing them that AI can deliver tangible positive business results. The most important thing to do in these instances is to present quantifiable figures to justify the investment.
Most AI pilot projects focus on avoiding catastrophes first, then achieving their goals later. For example, an image recognition system is required to avoid misclassifying persons or products in circumstances that could cause negative publicity for brands. In this particular instance, the purpose of the business needs to be considered.
This is why top executives often view AI initiatives as a way to exercise the prevention of damage. ROI metrics must link AI pilots to transition to a data-driven system successfully. Additionally, the initiatives need to show steady results over time. Only then can businesses continue to grow their efforts and prove that it is worth their investments.
- Democratize data
One of the most effective ways to get into the mindset of a data-driven one is to increase the accessibility of data across the entire organization. Data science teams that are centrally located do have their place. But this doesn’t suggest that companies delegate data analysis to just a few teams.
Embedded analytics is the best way to go. Integrating analytics into every company app lets companies draw insight from each employee, which can boost ROI. Although specific insights might steer teams on the wrong path because of poor analytical skills on the part of employees, however, the long-term benefits are enormous.
The companies can safeguard themselves against false data analysis by including experts in data science within each team. The data scientists can verify data analysis results and prevent inaccurate conclusions. It is impossible to predict the source of great insights. Data can be democratized to improve.
This strategy also helps to reorient all teams within the organization toward the customer. Teams can view customer data, analyze trends, assess their contribution, and calculate the impact of decisions in real time. This results in better products and better alignment with customers.
Data-driven for long-term outcomes
“Data-driven risk” is now a buzzword in many organizations because of an absence of planning. As companies adopt AI and other advanced technologies, an absence of data-driven procedures will fail and result in substantial failure rates. To be successful, businesses must shift their mindset towards data now.
Prioritize This Tool to Increase Customer Satisfaction amid a Recession.
While economists discuss whether or the possibility of there is a recession will be able to occur, a lot of companies are working on strategies if this scenario comes to fruition. They are adopting a “hurry up and sit” approach and focusing on becoming more efficient with their money.
The last few years have been transformational for many. Hopefully, your business has embraced specific customer experiences and digital transformation initiatives. Perhaps you’re in the lead, or many cases, the pandemic ignited an ember under your company as it did for many others. However, if you’re there’s no way to know, then the good news is that it’s not enough time to begin, and given the economy in a state of uncertainty, it’s an ideal time to start. The first step is Offering them what they need by offering the self-service option, which will allow you to operate more effectively from a technological viewpoint and help you navigate the possible recession.
Let your clients assist themselves literally.
We’re familiar with how sales were conducted through handshakes, order forms, and catalogs during lunch. The method was still in use before Covid-19, but things changed following the event — everything became remote, and many businesses had no option but to move to digital to stay ahead. With the upcoming economic slump, all eyes are on their pockets, so one of the best ways to improve your company and decrease sales costs is to ensure that clients have access to self-service options that allow them to purchase the items they require without assistance. Accessibility is essential, as is accessibility for every interaction.
It doesn’t matter where the starting point for your business is. Perhaps you’re still using hundreds or even dozens of field representatives that meet face-to-face with customers, or your customers utilize a call center where a person assists them in addressing their needs regarding products. What’s most important is where you should get A well-thought-out digital experience tailored to your customer’s requirements and accessible from any location to help them get what they want in real-time. Things that are simple to do should be simple. That means that if your customer needs to do something such as order a product, keep track of it, or change their payment information details, you can do all the above at the time and a convenient location for them. Thus making your online infrastructure for this is vital. If something is more complex and needs to be completed by itself, the customer could second think about their decision or even abandon the whole thing altogether since budgets are smaller; therefore, why would you waste time on something that’s not convenient? The digital upgrade also means fewer sales-related duties. But, with this lower-cost-of-sale idea could conclude, “are you suggesting we reduce the size of our sales staff?”
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