Modern Analytics groundbreaking “autonomous predictive analytics” recognized by world’s leading expert on advanced analytics
In early December, Modern Analytics was recognized by the world's leading expert on analytics, Tom Davenport, in an article he wrote for the Harvard Business Review. The article, titled "Move Your Analytics Operation from Artisanal to Autonomous," uses Modern Analytics as an example of how automated predictive analytics can significantly increase a company's propensity modeling output and value. The following excerpt highlights the section about Modern Analytics and Model Factory, but we encourage you to read the article in full.
As of August 2015 Forbes.com reported that over $7B was invested in the top 100 enterprise analytics startups and by my calculations, at least $700 million supported sales and marketing analytics focused firms.
It's an industry that has already surpassed the $125B mark and with emerging technologies like IoT and accompanying IoT BaaS (back end as a service) this industry will continue to grow and will become more and more competitive. It already resembles the hit fantasy drama television series with its warring factions, inside treachery, and power grabs...
The amount of information that's being created is elevating exponentially. It's almost impossible to wrap your head around it. Rapid advancement in data storage and data processing technology is enabling massive collection and archiving of information.
The "Big Data" phenomenon is creating the opportunity to acquire nearly unlimited insights. Analytics or "data science" can be used to predict what will happen and explain why it will. But many challenges to reaping benefits from analytics yet remain. One main issue: Data is siloed, disjointed, or disparate. Databases are not aggregated. Lots of bureaucracy and a lack of foresight can prevent different parts or divisions of organizations from sharing information. Not only has the volume of data skyrocketed, but the places where it's stored and the methods of collecting it have also expanded profoundly. So the question of the day is this: Are business leaders getting value out of all this data?
Both Mercedes and Google have developed autonomous driving, but has someone really made analytics autonomous?
Autonomous Analytics: Q&A with Matthias Kehder, CEO and Co-Founder of Modern Analytics
Autonomous analytics is not the process of automating data. It is the ability to connect to databases and figure out variables that need to be inserted and aggregated (using machine learning) to produce the best predictive solution autonomously, without human intervention. What we do is build a semi-exhaustive list of models and help our customers identify which of them to use now. The rest are stored for another day when they’ll be refreshed automatically as data is added.
Sales, the healthcare industry, product development, and hundreds of other business settings need predictive analytics to add precision. Why carpet bomb when you can use a smart bomb? To illustrate my point I'm going to stick within the sales and marketing world. When salespeople are hired they are commonly brought in for their rolodex. For some odd reason executives think that having a long contact list is going to be the secret sauce it takes to close deals fast. I hate to break it to you, that's not the case. Here's why...
Sales is the poster child for the phrase, "What have you done for me lately?" The only thing that matters to sales people and and sales managers is, "What did you sell this year?" This means that sales people don't have time to wait for when a prospect is ready to buy. Buyers buy when they're ready to buy. So this means most sales pro's need to find who will buy now and frequently this means people they know are not in the market (at least not this year) for what they're selling.
Win the Sales and Marketing Battle Before It’s Even Fought: Acquire Autonomous Data Modeling Technology
Sales and marketing is, in fact, a battle and a war. There are missions, strategies, tactics, battles, dealing with unforeseen circumstances, casualties, defeats, logistical challenges, adversaries, and the need to acquire and use various forms of intelligence (e.g. reconnaissance). Same case with the typical sales scenario, especially in the case of a complex sales processes.
Modern Analytics has developed, over twenty-five years, proprietary methods and machine learning technology to automate the process of generating data models. The status quo of data modeling at the time that this article was written is such: Data modeling is time consuming, expensive, capital intensive, data intensive, and difficult to achieve great model integrity. So much so that companies use this capability sparingly, solely for the most important business needs and not much more. Sometimes one or two models and in some cases, none at all.
Data scientists. Are they really scientists at all? When most people think of scientists they think of people who lock themselves in a room trying to solve the toughest problems we know. Cures for cancers, the next biggest things in polymers, spacecraft bus avionics, alchemy, stuff like those super-intelligent high school kids from the movie "Weird Science" would whip up.
In reality, data scientists exist to solve the universal, mission-critical business problems that companies contend with every day. Two of the most fundamental are these: How are we going to make money? And what can we do to minimize the risks and costs associated with doing business? This is what the CEO wants and this is what Chief Data Scientists and their teams need to figure out to be part of the senior leadership.
Machines can do things that weren't even dreamed of twenty years ago. Not only has the capability of computers risen sharply, the costs of using them has become very affordable and with the advent of cloud computing there is almost no need for capital outlay. This means that massive processing power and predictive analytics solutions can be brought in to have profound impact on controlling sales revenue. This is done by aggregating databases and running predictive analytics over the top to precisely identify each and every revenue opportunity regardless of the number of products, markets and applications. So if you're a company with multiple products and a slew of markets, this is your proverbial pathway to sustained profitability in the digital era in which we live and do business.
Post by David M. Raab - Remember when I asked two weeks ago whether predictive models are becoming a commodity? Here’s another log for that fire: Model Factory from Modern Analytics, which promises as many models as you want for a flat fee starting at $5,000 per month. You heard that right: an all-you-can eat, fixed-price buffet for predictive models. Can free toasters* and a loyalty card be far behind?
Modern Analytics is delighted to join the ranks of Marketo’s LaunchPoint Partners. This innovative partners program offers clients access to more than 100 applications and solutions providers of marketing services and programs.