Machine Learning and the Rise of the REEP: Role-Based Expert Enhancement Platforms

Scythe - the REEPer
Don’t fear the REEPer

Based on Amalgam Insights’ discussions with over two dozen enterprise application solutions over the past six weeks, we believe that a new generation of applications is starting to emerge. Machine Learning has led to the evolution of a new generation of platforms that are transforming expert productivity by providing insights through self-guided logic that improves over time.

Amalgam Insights calls these solutions Role-Based Expert Enhancement Platforms (REEP), an emerging technology made possible by the increasing use of machine learning and artificial intelligence in the business world. We believe that, in the short-term, the emerging value of machine learning will come not from generalized platforms, but from these role-based solutions that will greatly simplify finance, compliance, and sales enablement tasks. As companies start thinking about the role of machine learning in enhancing their organizations, Amalgam recommends that they consider these four key areas of benefit:

1) Role-Based: The REEP must solve a specific problem in the business world. Rather than simply provide a general artificial intelligence-based platform, programming language, or raw algorithms, the REEP is targeted to solve a specific set of problems associated with the business environment. Based on the challenges that machine learning and artificial intelligence is best enabled to support, Amalgam has seen an initial focus on financial tech, accounting, and text-based analysis for legal, reporting, and educational use cases. Over time, REEPs will be created across all areas where automated data, text, and transactional analysis can provide business value.

2) Expert: REEPs are designed to help subject matter experts and professionals to do a better job. Rather than replace experts, REEPs exist to support the grunt work, intensive data analysis, and cleansing necessary to identify insights. REEPs will increase in value when used by managers and experts with strong subject matter expertise, rather than low-level or untrained employees. Subject matter experts are better positioned to translate the output of REEPs into value-added insights.

This may seem straightforward, but this focus actually represents a sea change in enterprise technology. Traditionally, enterprise software has been designed either for IT expert admins or for operational personnel to actually use. Executives and key managers may use these technologies to get a pulse on the business, but rarely use the software on an hands-on basis. This new generation of REEPs is built for the business manager, not the technology manager, and represents both a new value proposition and use case for enterprise technology.

3) Enhancement: By targeting relevant data based on intelligent machine learning capabilities, REEPs provide a shortcut to new insights rather than forcing experts to spend a majority of their time simply looking for the needle-in-a-haystack eurekas or risks that can potentially lead to Black Swan effects. By shifting Expert time from analysis to action, REEPs enhance the efficacy of the best and most productive employees in a business.

4) Platform: REEP platforms are not stand-alone solutions. They must be able to connect with all relevant applications and data sources associated with the Role as well as new data sources identified by Experts on a going-forward basis. Over time, REEPs are designed to be extensible as roles and business needs inevitably evolve over time. To be a true REEP, an enterprise solution must have open APIs and the ability to support third-party software that accesses the platform.

Amalgam Insights notes that REEPs will eventually replace embedded BI and legacy ERP use cases across the enterprise as employees start to understand how to replace the granular and manual data analysis associated with business intelligence with the algorithmic and context-driven work made possible through machine learning and artificial intelligence capabilities. However, this shift requires experts to identify and outsource the basic logic used to conduct the most time-consuming parts of their jobs. As this realization occurs and REEPs become more prevalent, Amalgam predicts that the REEP model will define the next generation of enterprise applications that provide transformational value.

Amalgam recommends looking at the following solutions as representative examples of REEPs that solve enterprise departmental needs (Note: this list is far from complete, but represents Amalgam’s view of best-in-breed execution for this emerging set of companies):

Finance and Supply Chain: Infor, which supports over 5000 APIs through its Intelligent Online Network (ION) Platform as a Service. This flexibility comes out of need, as Infor supports configurability on an industry-specific basis. The combination of ION and Infor’s Coleman artificial intelligence effort will provide highly granular functionality for the post-ERP world where REEPs will take over. Infor received a $2.6 billion investment from conglomerate Koch Industries in November 2016.

Finance: Mindbridge.AI, a financial data auditor that uses artificial intelligence to target and prioritize the specific regulatory and financial issues that have the greatest impact on an organization. Mindbridge goes to market both independently and with partners such as Thomson Reuters. Mindbridge raised a $4.3 million seed round in June 2017.

Sales Enablement: In this space, two emerging startups stand out: Gong.io and Tact.ai.

Gong.io focuses on Conversational Intelligence: analyzing specific behaviors and alerts within each sales call to understand and summarize the most important aspects of each call. By doing so, Gong supports improved sales coaching and accelerates the ability to support advanced exception handling and one-on-one messaging challenges. Gong last raised a $20 million “A1” round in July 2017.

Tact.ai focuses on being a personalized sales assistant for each sales executive by answering direct questions via app, text or Alexa-powered speech. It serves as a bi-directional solution where sales reps can verbally update CRM and then directly ask questions without having to directly work with CRM. In addition, this solution also will connect related information, such as LinkedIn profiles, to relevant contacts and locations. Tact last raised a $15 million B round in December 2016.

Amalgam also believes that there are more general platforms such as GoodData, IBM Watson, and Salesforce making progress towards creating REEP solutions. In future posts, Amalgam will cover how these solutions have taken a REEP approach in their product development.

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