ERP solutions won’t necessarily go away but a new generation of solutions gives us clues as to where major productivity gains will come from.

Most ERP systems are stuck in the past or are improving incrementally. The next wave of productivity savings for businesses will likely come from technology vendors you’ve never heard of. They’ll come from firms unfettered by traditional ERP transaction processing systems. They’ll come with a different business viewpoint and solve very different problems. It’s all these differences that will make this new productivity wave come to life.

New vendors are designing solutions that:

  • Use massive datasets from the get go. They’re not limited to the constrained, highly structured accounting and other internal transactions that ERP solutions use. They use giant social sentiment, sensor, weather, email, graphic image and other data stores to get more of the ‘picture’ than an ERP solution gets within the four walls of a typical enterprise.
  • Complement, not replace, ERP products. ERP is good for basic, internal transaction processing but it wasn’t designed for the age of large data sets, social media, personal digital exhaust, etc.

The new wave of business productivity will come from:

  • A better level of asset utilization/optimization across every major spend category including people and machines.
  • Reduced energy costs.
  • New customer insights and improved employee engagement.
  • Insights identified from all-new metrics.
  • Machine generated predictions and recommendations.
  • Solutions that are made substantially smarter via the addition of deep insights gleaned from the perusal of and access to large amounts of external and non-transactional data
  • A focus on new operational metrics that go way beyond old-school metrics like those in the DuPont ROI model
    The massive application of new technologies like machine learning, algorithms, in-memory processing, etc.

A New Aera

There are several all-new firms creating something different. These aren’t ERP replacements or alternatives to ERP. These are new solutions that mix old (i.e., ERP) data with new data such as sensor, weather and other big data items. Along with this data, they’ve added new technologies like machine learning, deep vertical knowledge, in-memory cloud technology and more.  To this list of new companies like C3IoT and Uptake, let’s add Aera Technology.

Aera, nee FusionOps, recently got a $50 million VC investment and a new CEO, Fred Laluyaux, who, until recently was  the CEO of business planning/forecasting software firm Anaplan. Laluyaux also has some serious ERP chops in his background as he was an SAP executive.

 Aera is how the software answers a user’s question like “What’s our cash balance?”. Aera doesn’t just serve up a direct response to the question. It also interrogates the question and the immediate answer to anticipate the next 1-2 questions you might have.

For example, if it thinks you’ll not be happy with the cash balance, it will volunteer a number of cash improvement ideas. It might, for example, suggest following up on a couple of large outstanding customer receivables. Or, it could also recommend the liquidation of some excess inventory. The software tells the user the dollars involved in these different scenarios and it awaits the user’s instructions with which it can complete.

What’s happening behind the scenes is that a natural language processor interrogates the voice question, it then maps the request to a taxonomy of values found in the company’s data stores (e.g., ERP data) and, via integration technology, it serves up the initial response.

That’s when the fun gets started. The software reviews the answer and makes a judgment call. It decides, if you will, whether the answer is good or bad news, and suggests ways to either minimize the adverse effect or to continue the positive trend. It does this because someone has taken the time to create rules and workflow logic behind these kinds of queries. Should the user choose one of these suggested courses of action, the software can help complete the business event as the pre-programmed workflow is ready to do so.

If you think the voice-enabled approach sounds too much like a consumer-grade Alexa app, then simply turn the interrogation logic on to the real-time data coming from sensors, ERP software and other sources. When an anomalous event becomes apparent, rules kick in and options are presented to business users. Management, in the future, will be less about finding anomalies and more about fixing or exploiting them.

The analogy that Aera customers use is that systems need to be like a self-driving car. The system is always on and always recommending course corrections in real-time. How much better would a value chain be if companies tied their financial planning activities to external data sources such as customer growth, seasonal sales, sales of competitors’ products, retailer point of sale data and more? Minor changes in some aspect of the value chain could be picked up, analyzed and then the manufacturing and distribution aspects of the company are tuned to achieve optimal revenue and profitability.

This kind of external data-driven analysis is not what ERP has been about. For example, do ERP systems monitor weather patterns and recommend shifts in production and distribution to accommodate changes in demand due to an upcoming hurricane hitting the southeast U.S.? No – that’s why a newer generation of solutions and the value they throw off is needed.

Aera is already capturing the attention of large firms like Columbia Sportswear and Merck KGaA.  Why? Businesses are looking for ways to automate a number of decision making aspects of their supply chain and other processes.

Aera organizes around Skills. It has skills for manufacturing performance, predictive demand, delivery optimization, revenue maximization, market share growth, predictive sourcing and margin optimization. Customers can take advantage of a number of pre-built dashboards, integrations and more to jumpstart their new productivity improvements. For example, the manufacturing performance skill uses machine learning to predict batch failures. There are more than 20 different algorithms in the predictive sourcing skill. There are even AI tools creating pricing recommendations in the margin optimization skill.

Old challenges

Not surprisingly, Aera and its competitors are finding that getting useful, viable data out of ERP solutions is not easy. Companies may have:

  • More than one ERP solution in use at their firm

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