"Algorithmic business is here," said Gartner VP, Peter Sondergaard, "Can you calculate the value of relationships with 3 billion people using smartphones? Can you calculate the value of access with 30 billion things? Can you calculate the value of trust in your relationships?" Well, the A2 community can, so good on us.
What do we do about it? Gartner is continuing to talk about bimodal (thatís their term for an IT department that has two parts -- one to keep the lights on and one to innovate), except now they're talking about a bimodal business. "New businesses are designed to combine the physical and digital worlds. Moving at two speeds. Business itself is now bimodal, "Sondergaard said, "Digital does not compete with analog. They work together. Organizations are creating separate business units to concentrate on digital."
One example they gave of this in practice is Williams-Sonoma. In an era when most retailers have been losing share to online stores and brick and mortar stores have suffered, half of Williams-Sonoma revenue is from digital. They took share from others. They didn't do this by reworking their brick and mortar stores. Instead they built a separate digital strategy.
"Your approach to digital reveals a lot about your maturity with data," Sondergaard said, "Consider where you start. An established business model attempts to adapt to the customer needs at the moment. They build processes on top of old processes. In contrast, digital organizations start with customer behavior. They don't ask what the customer wants, but what the customer does."
That's where algorithms come in. According to Sondergaard, "The new platform is less on data gathering and more on intelligent algorithms that react to the data." That data is coming from what they call the "digital mesh," a constantly growing network of connections between people, devices, and algorithms. And by necessity, more and more of those interactions will involve smart algorithms to keep up with the pace of business. You simply can't wait for humans to check all your data and make a decision. You'll need algorithms for pricing, stocking, shipping and a million other tasks that can't wait for a human to parse enormous chunks of data.
"By 2020 smart agents will facilitate 40% of customer interactions," Sondergaard said. By that he means intelligent devices like Cortana, Siri and Watson (and less chatty ones) actually making decisions for us. Think the Amazon "people who liked this, also liked that" concept except the machine may actually do the purchasing on our request.
I'll have more coverage on some of the developments and changes in BI, analytics, and data in the coming weeks, but for now, Gartner suggests a couple of things you need to do to get ready for the age of algorithms.
First, you need to inventory your algorithms. Every business has a secret sauce whether it is a real recipe for a product like Coke or the analytics you use to get your product to market faster than the competition. Outline those algorithms that are most important to your business.
Then assign ownership of those algorithms. Gartner suggests these be owned by the Chief Analytics of Chief Data Officer. Most importantly, they need to be nurtured as the key to the business.
Most importantly, you need to decide which algorithms to make public and which to keep private. Public? Yes, public. Gartner believes that the algorithmic economy is going to be one of give and take and that the giving and taking of algorithms and data sets will multiply their effect. What you really want to do is place yourself in the center of a dense digital mesh, a network of customers and machines around a product.
As an example, Tesla made their patents for super chargers available to the public. They didn't do it because they were nice. They knew research in super chargers would help them. And in fact, Ford and Toyota have not only shared their data on super chargers but have opened other patents as well. A perfect example of multiplying the effect of data and algorithms to the economic benefit of all.
But whether you're ready to throw your algorithms out to the public or not, this is a key moment for the analytics community. Analytics just got put on the top of mind of CIOs all across the country. Are you ready to respond with real-time analytics, prescriptive analytics, machine learning, and AI? If not, it is time to get ready.