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This article was written by Prasanna Dhungel, mmanaging partner of GrowByData.
Companies today have a lot of data, a modern data warehouse, AI (artificial intelligence) tools and beautiful visualization platforms. Yet users in small and large businesses around the world are frustrated by their inability to quickly get their questions answered from their data.
We now have data everywhere and we are drowning in a sea of data. We have gone from a data-poor society to a data-overwhelmed society struggling with information overload. But users simply want answers from their data. Marketers, for example, want to know when a competitor’s product is distracting from its brand. Doctors want to give specific advice to their patients on what to do based on their medical records. The examples are numerous, but the need of each user is the same: to obtain answers to his questions.
The obvious question is: how did we get here?
Over the past decades, we have continuously digitized in an increasing number of industries. The internet and mobile phones have made publishing easy and we now have data across text, images, sound and video stored in accessible cloud servers. We have warehouses like Azure and Redshift, and analytics like Big Query. These are exciting times for us data professionals. Unfortunately, I’m afraid we’re getting caught up in the tool hype. We continue to offer more and more figures, graphs and tables to our users. This is precisely the problem. We do not offer guidelines on what to do. According to Dell’s study, “data overload has become a significant barrier to transformation.”
Data users don’t ask if we use the latest AI or all possible data related details. When we share large volumes of data, they push back saying, “I don’t know what to do with all of this. Can you give me simple, practical advice without overwhelming me? » Users want to protect themselves from data overload.
In retail, brand managers want to understand if and how shoppers see their products. If a brand isn’t visible on Black Friday, that’s a huge problem. If a brand’s promotions, prices, or shipping costs aren’t as compelling as those offered by competitors, shoppers won’t buy. You can share prices, reviews, visibility and more with a brand manager. However, details alone are not valuable. You really need to let the brand manager know when a competitor is taking their place or offering a better deal.
In healthcare, electronic medical records store patients’ medical conditions, medications taken, lab results, X-rays, and more. However, the physician should know which patient to remind to schedule a mammogram, colonoscopy, or other wellness procedure. The doctor must know which patient is likely to become ill and requires intervention. If a home monitoring device detects a sick patient falling, the device should notify 911 to take them to the hospital and notify their doctor. All of these values must be provided from the data.
In accounting, managers want to understand and gain insight into financial ratios. Imagine a business owner not quickly knowing that cash is running out due to poor accounts receivable collection. A customer service representative should inform a customer that they will not receive service until payment has been received.
Our industry is inundated with articles about data tsunami, overload and fatigue. Users want to understand what happened, why, and what to do next. Gone are the days when you could tell your users that you will be back with answers tomorrow. Outdated data is not useful. Users demand answers now.
The right question is: how do we as data professionals meet these user needs? I believe we need to do the following:
1. Deeply understand the needs of data users
Creating the right response that the user finds impactful requires many conversations and product iterations. We need to ask users directly what they find valuable. Usage data is a good indicator for understanding customer adoption. It is critical to understand whether customers correlate ROI with the information presented.
2. Engage an interdisciplinary team to create ideas
We want secret key performance indicators (KPIs) that allow users to spot opportunities to increase revenue and reduce costs. To remain unbiased in a data-driven mindset, we need cross-disciplinary team members including; colleagues from data science, customer success, content marketing and design – to talk about customer needs.
3. Combine macro trends with notable events
We need to provide high level trends with sharp trends in interactive visuals. Current tools like Tableau and Google Data Studios visualize stories in data. To gain user trust in our data, we need to be transparent about how we generated our analysis.
4. Allow data users to access information about the tool of their choice
User preferences have evolved from “I will log into your software to understand what I need to know” to “Alert me on my phone to tell me what to do only when something important happens. product”. Today, data users ask devices like Alexa and Google Nest to remind and notify them of news, time, weather, and more. This means companies must push information to a data user’s application of choice, such as podcasts, digital assistants, YouTube videos, email, etc. Wherever our users are, that’s where our solutions need to be.
Advances in big data, cloud computing and analytics are giving us tremendous power. To share these benefits with our users, we need to deliver impactful, simple and easy-to-use information quickly and affordably using a tool of choice for data users. Only this will provide the value that today’s data users demand.
Prasanna Dhungel is Managing Partner of GrowByData, a marketing intelligence company serving advertising agencies and global brands. He has two decades of experience delivering data insights to thousands of users worldwide in retail, advertising agencies and healthcare.
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