Although it was once considered the be-all and end-all for business success, data is now creating big problems for companies, as they fight to manage the incredible amount of data in their organization.
“It’s the data that encompasses all of the customer information, or product information, or reputational information or otherwise, that needs to be harnessed to drive value,” says ElectrifAi CEO Edward Scott. “That’s what the companies are struggling greatly to do.”
Large enterprises might have the resources to hire data scientists to combat the problem, but what about mid-market companies? These businesses often don’t have the resources to hire an internal data science team, which makes it difficult to compete with bigger, better-funded enterprises.
But this doesn’t mean that mid-market companies are doomed to a data-less future. Prebuilt machine learning, natural language processing, and computer vision solutions from ElectrifAi are making it possible for midsize companies to mobilize their data, optimize operations, and improve their top line and bottom line.
Global AI solutions experts like Edward Scott and ElectrifAi can help mid-market companies leverage their data to drive business value in just six to eight weeks.
The Challenges Mid-Market Companies Face
Data value is a universal struggle for both enterprises and small and medium-sized businesses. Unfortunately, mid-market companies have fewer resources to tackle the data problem.
The paradox is that more prominent companies often have such convoluted internal data that they can’t readily turn it into anything actionable. Since mid-market companies have fewer stakeholders, they have agility on their side — but that doesn’t make up for lack of resources.
Some mid-market companies are able to limp by without solving the fundamental problem with their data, but over the long term, that will lead to their undoing. According to a report by global management consulting firm McKinsey & Company, organizations that invest in data are 23 times more likely to acquire customers and 19 times more likely to be profitable.
“For the medium-size companies, they are at an existential moment,” Scott explains. “The guys who do nothing are going to go out of business or suffer substantial valuation limitation and enterprise growth limitation. We believe that data is the key to enterprise valuation growth.”
How Prebuilt ElectrifAi Solutions Give Mid-Market Companies A Leg Up
Midsize companies need to turn their data into a strategic weapon, but the big question is: “How?”
“With the medium-size companies, some of which are Fortune 500 to Fortune 1000, many of them don’t have data engineering or data science teams,” Edward Scott says. While middle-market companies don’t have the luxury of hiring data scientists, many rely on outside vendors such as ElectrifAi. This helps middle-market companies succeed in spite of competition from large, well-heeled competitors that can afford to invest in data science.
Edward Scott shares the three ways ElectrifAi’s prebuilt solutions help mid-market companies find tangible results from their data.
Most companies assume their data is inherently clean and actionable, but in Scott’s experience, that’s far from the truth. Mid-market companies often have missing or misleading data, outliers, and multiple sources that make it impossible to draw accurate conclusions.
It takes time, but mid-market companies must use AI solutions to clean, organize, transform, and merge their data first. Even though ElectrifAi delivers time to value in six to eight weeks, Edward Scott shares that his team spends the bulk of that time cleaning and transforming client data. “The ugly secret is, the data transformation is three to four weeks of that; machine learning and training of the model and the deployment is the balance,” he explains.
To speed up the process, ElectrifAi uses machine learning models to detect data quality issues. For example, the product can spot misspellings to merge duplicate entries as well as classify spend. The product identifies problems with the data source not only upfront, but on an ongoing basis to ensure that the company’s data stays clean.
But clean data alone isn’t the answer. Information is still up to interpretation, which is why mid-market companies still need experts who understand the business, technology, and data to draw accurate conclusions. “Tools are good to help you speed up the process, but you still need to put effort into this,” explains Edward Scott.
By hiring an external vendor like ElectrifAi, mid-market companies get the instant expertise they need without the expensive cost of investing in an internal science team. There’s no need for an ocean of data, either: Six to seven data points are usually enough to solve pressing business problems.
And you don’t need to move all your data to AWS or Snowflake before reaping the benefit. “It’s great if the data is already in a data warehouse of some sort, but not required to quickly drive business value”, Scott says.
Prebuilt solutions help mid-market companies save time and money, but they aren’t generic: ElectrifAi still customizes every machine learning solution to fit client needs. ElectrifAi calls this Last Mile Ai and Consequential Ai.
Scott’s team leverages their domain knowledge to create reusable code, which they can then be customized to fit each client’s specific needs — that’s how ElectrifAi is able to drive business value so quickly.
“We minimize the customization with the client’s data. That’s what we’re doing in that two- to three-week period. That’s part of our scalability, in addition to the knowledge reuse, focus on industry, focus on use cases,” Edward Scott explains.
In an effort to drive transparency, mid-market companies have the freedom to view and modify the ElectrifAi code as they see fit. “Why wouldn’t we be radically transparent with our clients to help them solve their business problems? It’s not about the tech or the alphabet acronym of the day. It’s about solving the business problem,” he says. “We make it easy and transparent for our clients. No black boxes,” Scott explains.
Unleashing Data’s Potential For Mid-Market Companies
Data alone can’t save midsize companies from the whims of inflation, supply chain delays, or changing consumer demand. While large enterprises have the resources to act on their data, mid-market companies often struggle to get by in today’s challenging business environment.
This is why prebuilt, industry-specific machine learning and NLP solutions are so necessary. Through cleaner data, domain expertise, and careful customization, solutions like ElectrifAi give mid-market companies a true competitive advantage. “The solutions that we’re talking about today drive your top-line revenue, optimize your operations, and reduce costs. That’s what Consequential AI really is,” Edward Scott concludes.
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