How to Get the Most from Microsoft Dynamics Analytics
Highlights
- Microsoft Dynamics 365 business intelligence apps are more than a convergence of customer data and analytics processing. They create a synergistic relationship which shifts customer engagement from reactive to proactive and elevates data from a byproduct to an asset.
- Most companies are data rich and information poor. It's an unfortunate paradox, but data is both their most unused and under-capitalized asset. Microsoft offers a progressive suite of analytics tools to convert data into actionable insights.
- Business intelligence is one of only four sustainable competitive advantages. It's sustainable because making better business decisions never loses its value.
The Microsoft Dynamics 365 Analytics Tools and Journey
Many executives and CRM software users would argue that the business intelligence (BI) derived from CRM software is far and away the greatest value of CRM. CRM software by itself is mostly a customer data repository. But with BI tools, CRM software becomes a predictor of customer behaviors, creator of customer insights and facilitator of customer and company objectives. CRM software is a tool. Information is an asset.
Cloud computing, cost-effective data storage, integration tools and BI apps designed for business analysts and power users have morphed with the Microsoft Dynamics 365 software to make more types of information reporting available to far more companies.
Microsoft offers a large and growing BI tools portfolio. Trying to make sense of it from a technical perspective doesn't really make sense for most businesses. A better method is a phased approach to increase information value with maturity. The below diagram shows a progressive approach that aligns with the business intelligence continuum.
Descriptive Analytics
Descriptive reporting is historical reporting. It accumulates CRM entities and activities and displays them in simple lists, reports or CRM dashboards.
Salespeople spend significant time viewing accounts and contacts. Marketers view leads and campaigns. Customer Service reps view contacts and cases. The primary Dynamics CRM software tools for these entity lookups are views and lists. When shadowing users I notice they do a lot of scrolling to find what they are looking for. Some minimal training on saved query parameters, filters and search options saves these users time on highly repetitive tasks.
Another efficiency opportunity is to align repetitive activities into work streams. Dynamics 365 has an impressive guided process builder.
Unfortunately, most Dynamics CE users leave the default process guide in place, rather than modify it to streamline their actual activities and view more accurate information. When correctly designed, the process flow control at the top of forms is very effective in adding context to otherwise static records.
Instead of just viewing any particular (account, contact, activity, opportunity, case, campaign, etc.) record in isolation, the process flow visualization shows the record history (how it got to its current state) and destination (what steps are next to achieve the desired outcome).
Process flows define and display Stages and Steps at the top of each form. Each Stage contains a series of steps. Each step is a field or activity where data is defaulted or entered. Processes can include internal controls or guardrails such as stage-gating, which requires that certain steps be completed before subsequent steps can begin.
Designing streamlined business processes and delivering information in context (including where it's been and where it's going) is much more insightful than static records and acts as a proactive guide to make information more actionable.
Diagnostic Analytics
Progressing to diagnostic reporting reveals why something happened.
If properly designed, it can also advance information reporting from being merely interesting to actionable.
For Dynamics 365 CE (Customer Engagement) users the go-to diagnostic reporting tool is Power BI. This tool facilitates user generated, agile data analysis with self-service analytics managed in the cloud for collaboration and sharing.
Natural Language Processing (NLP) is the Q&A capability that makes Power BI available to the masses. NLP is a speech recognition capability for Power BI to read, decipher and respond to the human language. It's the human to computer communication bridge that allows any employee to ask a text or voice question and get a diagnostic response.
A frequently used alternative to Power BI is dynamic downloads to Excel. However, while Excel is probably the most used self-service BI tool in the world, it limits information sharing and poses data integrity concerns.
We've found some additional measures make Dynamics reporting more actionable. For example, Dynamics dashboards surface statistics. By identifying role-based key performance indicators and prioritizing the output, it changes the information from loosely categorized listings to stressing what needs to be done first, then next, and so on. Ranking of KPIs in dashboards identifies the importance of information.
Predictive Analytics
The jump to predictive analytics shifts the company's vision from hindsight to foresight.
Microsoft Dynamics analytics include many basic but extensible predictive capabilities.
- For salespeople, Dynamics CE offers machine learning templates to score leads and sale opportunities, identify opportunities at risk, suggest next best action, recommend talking points, and make intelligent product recommendations.
- For Customer Service Representatives, Dynamics 365 machine learning templates can auto-suggest Knowledge Base articles to resolve cases, predict customer churn, use bots to offload simple and repetitive customer requests and apply natural language technology to access customer data.
- For marketers, Dynamics 365 CE offers Market Insights to harvest social media or machine learning to calculate offer responses and campaign conversions.
To illustrate a representative sales scenario, Dynamics CE Predictive Lead Scoring is a machine learning predictive scoring calculation that scores leads on a scale of 1 to 100 based on their likelihood to become an opportunity.
It is an out-of-the-box machine learning template that considers attributes from related entities such as Contacts and Accounts and not just attributes of the Lead entity. Predictive scores can also illustrate the top factors influencing the score. With Predictive Lead Scoring, sales reps can prioritize their efforts on deals that have the highest likelihood to convert.
Sometimes predictive analytics solve some lingering problems. If accurate sales forecasts are a challenge the Dynamics Sales Insights can objectively predict future revenues. This analytics tool supplements seller-generated forecasts with predictive modeling. It applies vast amounts of historical data to replace bias or wishful thinking with actual experiences. This type of pipeline reporting also permits what-if modeling using hierarchies, filters and data modifications (i.e., including or excluding committed, stretch or omitted sale opportunities.)
A customer Service scenario may be to evolve from reactive to proactive customer support. Instead of waiting for problems to happen, service centers can use telemetry, sensors or IoT to become proactive. The ability to acquire more data from products, customers and social networks creates a digital feedback loop to use data for predictive analytics. Data precedes problems. It finds anomalies and imminent conditions that can detect problems before they occur.
A common tool to modify or create your own Dynamics predictive capabilities is the AI Builder. It is part of the Microsoft Power Platform and like other apps in this suite is a low-code tool designed for business analysts or power users.
Most every company is or aspires to be a customer-centric company. An initial step to meet this goal is to acquire customer intelligence and achieve a 360-degree customer view. Dynamics 365 Customer Insights is a Customer Data Platform (CDP) used to unify all your customer data from across disparate locations and create a single view of customers.
The CDP can consolidate transactional, observational, and behavioral data in near real time with prebuilt connectors to keep CRM Account and Contact records up to date. This type of data transformation is defined in a CRM data strategy and processed with tools connected as a data refinery as shown below.
Prescriptive Analytics
There's some Dynamics CRM software tools overlap between predictive and prescriptive analytics. It's the business use case more than the tool that advances to prescriptive reporting.
A CRM analytics strategy is needed to achieve this level of information intelligence.
Dynamics is infused with a platform-based artificial intelligence suite that includes infrastructure, services and tools.
The AI infrastructure runs on the Azure cloud. This allows users to easily provision, trial, prove and scale advanced solutions.
AI Services are broken down into three areas of Cognitive, Machine Learning and the Azure Bot Service. Cognitive Services are all about vision, speech and language. These services enable visual perception, speech recognition, and translation. Machine Learning services enable advanced decision-making capabilities. The AI Tools connect both Data and Services.
CRM AI use cases with prescriptive capabilities from Microsoft for Dynamics 365 Customer Engagement include predictive lead and opportunity scoring, relationship analytics, insights from LinkedIn InMail, talking points (recommended insights), Who knows whom (recommended connections) and Notes analysis. Microsoft also delivers role-based AI use cases.
For example, AI capabilities for sales managers may include sales performance scorecards, team performance analytics, sales data Q&A, lead prioritization, pipeline analysis with relationship health and conversion intelligence.
The Future of AI and Analytics Software
Most current AI applications are built as add-ons to CRM software. However, as companies realize that information is their most valuable asset, they also recognize analytics must be a core system, not an add-on to a business application. Companies replace their applications, but their information is lasting.
Microsoft Dynamics architecturally shifts AI and their BI suites from CRM software bolt-ons to underlying infrastructure. This accelerates the evolution from a customer data repository to a creator of customer insights. This evolution will mark a profound shift from putting data into a system to getting value out of the system.