2024 is shaping up as a transformative year for the financial services sector, marked by technological strides and innovative trends. Our industry experts helped to provide valuable insights that unveil a tapestry of trends reshaping the industry this year.

Client Retention and Personalization at Scale

Financial services institutions are increasingly recognizing the importance of understanding diverse client needs and fostering relationships across different age groups. Prioritizing client-centric approaches, such as tailoring services across generations and bolstering loyalty through personalized experiences, is crucial for maintaining a thriving client base.

Moving forward, institutions should focus on:

• Implementing advanced data analytics to gain deeper insights into client behavior
• Investing in robust customer relationship management (CRM) systems to centralize client data
• Embracing omnichannel engagement strategies to deliver seamless experiences
• Prioritizing customer education and financial literacy
• Adopting a human-centered design approach
• Regularly monitoring and measuring client satisfaction through feedback mechanisms

See Also: Perficient Recognized in Forrester’s The Customer Experience Strategy Consulting Services Landscape

Regulatory Compliance and Operational Resilience

Thus far in 2024, institutions have observed an increased emphasis on regulatory compliance and operational resilience. With cybersecurity threats on the rise and regulatory requirements becoming more stringent, institutions are compelled to integrate advanced technologies and proactive measures into their operations.

To navigate this landscape effectively, institutions should consider the following action items:

• Adopt robust risk management frameworks
• Enhance regulatory reporting capabilities
• Conduct regular compliance audits and assessments
• Embrace RegTech solutions
• Foster a culture of compliance and accountability
• Collaborate with regulatory authorities and outsource risk and compliance experts

Our client needed end-to-end risk and regulatory support, including business-as-usual activities, continuous risk and control assessment, and business continuity management. ​ We embedded a team of experts to support operations in risk and control self-assessment, control testing, issue management, business continuity, and third-party risk management. ​ Our continuous services equip the bank to proactively address and uphold regulatory compliance, manage vendor risk, and expedite key insights and reports.​

Learn More: Strategies + Solutions to Ensure Regulatory and Compliance Excellence

Data Analytics, Artificial Intelligence, and New Technologies

The financial services industry is undergoing a profound transformation driven by the widespread adoption of data analytics and artificial intelligence (AI). These technologies are revolutionizing traditional practices, enabling institutions to enhance efficiency, improve decision-making processes, and deliver more personalized services to customers.

With AI’s impact extending across critical areas such as credit scoring, embedded finance, debt collections, and fraud detection, financial institutions are increasingly leveraging these capabilities to stay competitive in the evolving landscape.

To effectively harness the potential of data analytics and AI, institutions should:

• Implement advanced data analytics and machine learning techniques to optimize operational processes and extract actionable insights from large datasets.
• Explore AI-driven credit scoring models to enhance risk assessment, improve lending decisions, and mitigate credit risk.
• Embrace embedded finance solutions by integrating financial services seamlessly into non-financial products and services, leveraging AI algorithms to personalize offerings and enhance customer experience.
• Adopt AI-powered debt collection strategies to optimize collection processes, prioritize accounts, and maximize recovery rates while minimizing operational costs and customer friction.
• Deploy advanced fraud detection systems leveraging AI and machine learning algorithms to detect and mitigate fraudulent activities in real-time, safeguarding against cyber threats and financial risks.

See Also: Perficient Recognized as a Major Player in IDC MarketScape for Cloud Professional Services

Sustainable Business Model

There’s a noticeable shift towards sustainable and socially conscious business strategies within the financial industry. Recognizing the importance of sustainability for both investors and stakeholders, institutions are exploring ways to enhance their business models while mitigating environmental impact and promoting social responsibility.

To properly navigate this evolving business model, institutions should consider the following:

• Develop comprehensive sustainability strategies that align with organizational values and objectives.
• Offer sustainable investment products and services that meet the growing demand from socially conscious investors.
• Enhance transparency and disclosure practices to provide stakeholders with clear and accurate information on initiatives and performance.
• Engage with clients and stakeholders to understand their sustainability preferences and incorporate feedback into product development and service offerings.
• Foster a culture of sustainability throughout the organization by providing training and education on sustainability principles and encouraging employee participation in sustainability initiatives.

Discover Your Potential with Perficient

By embracing these themes, financial institutions can navigate complexities and unlock new opportunities for growth and resilience. Ultimately, staying ahead of these trends is imperative for those in the industry to meet evolving client needs and to continue thriving in the sector.

Perficient combines strategy, industry best practices, and technology expertise to deliver award-winning results for leading retail and commercial banks, wealth and asset management firms, capital markets institutions, and payment and fintech organizations:

• Business Strategy + Consulting: Harmonize transformation initiatives to respond quickly to industry changes.
• Data Intelligence + Analytics: Harness reliable data and unlock financial and operational insights.
• Technology Modernization: Maximize technology to create experiences that meet evolving expectations.
• Risk + Compliance: Control risk, meet regulations, and stay ahead of change.
• Operations: Empower employees to drive business outcomes.

We are a go-to partner for technology platform leaders, recognized by analysts, and have been trusted by 18 of the 20 largest commercial banks, 16 of the 20 largest wealth management firms, and 25+ leading payments and card processing companies. 

Explore our financial services expertise and contact us to learn more.

Data plays an essential role in today’s digital economy and keeping up with modern data management processes is key to staying competitive. In fact, enterprises with advanced data practices are more productive, innovate faster, are able to enter new markets quickly, and are more likely to be directly monetizing their data compared to their less-mature peers. But achieving that level of competency often requires the assistance of a data management service provider.

Partnering with a data management service provider can help your organization:

• Establish a strategy and operating model for data
• Build an enterprise data foundation
• Mature and scale data governance

In the Now Tech: Data Management Service Providers, Q4 2021 report, Forrester defines data management service providers as:

“Service firms that provide talent, technology, and best practices through strategy and deployment partnerships in order to improve an enterprise’s use of data management to drive insights and business results.”

Forrester Now Tech: Data Management Service Providers, Q4 2021 Report

Identifying the right service provider to partner with can help you realize the benefits of data and increase your data competency.

In the report, Forrester segmented vendors based on market presence and functionality. Market presence was determined by data management service revenue and vendors were placed into one of three categories: large established players, midsize players, and small players. Functionality was based on varying capabilities and broken down into four segments: platform providers, data and analytics services, specialized service providers, and system integrators.

Each vendor was asked a number of detailed questions about their services, including geographic presence, industry expertise, and data management experience and expertise. Based on the responses, Forrester supplies information about these service providers to help you determine the best vendor for your data management needs.

Perficient’s Primary Functionality Lies in Specialized Services

Forrester listed Perficient in its midsize category ($100M to $1B in annual category revenue) as a specialized service provider. According to the report, “Specialized service providers concentrate on data and governance foundations. These firms have extensive data engineering, data management, data security, and data governance expertise for data-driven initiatives prioritized by CIOs, chief data officers, and enterprise architects. Engagements focus on data strategy, data architecture, data operations (DataOps), and data governance, helping enterprises transition into insight-driven businesses.”

Perficient’s listing in this Now Tech includes our geographic presence (100% North America); industry focus areas (healthcare and life sciences, financial services, and retail); and sample customers (Novant Health, StorageMart, and United Wholesale Mortgage).

Perficient’s Approach to Data Management

One of the greatest attributes of data is that it becomes more valuable the more you use it. But seeing that value is difficult if you’re not managing your data properly.

As a specialized service provider, we’re helping leading companies create actionable business insights based on accurate, scalable, and comprehensive data.  We bring the thought leadership, technology expertise, and processes to help our customer become data-driven organizations capable of leveraging data for competitive advantage. We do this through:

• Taking the time to understand your business
• Collecting, organizing and managing data from all over your organization
• Delivering insights via intelligent applications
• Deploying data and insights to any user via any interface

Learn More about Perficient

We’re ready to help you realize the benefits of data no matter where you are on your journey. Our experience, our technology partnerships, and most importantly our people are what make us a great partner. Visit us on Perficient.com and learn more about how we can help you master the realities of the data-driven world. And listen to the Intelligent Data Podcast where we interview thought leaders on a variety of topics around using data and technology to reshape your business.

You can read the entire Forrester Now Tech: Data Management Service Providers, Q4 2021 report via the Forrester website where it’s available to Forrester subscribers and for purchase.

MicroStrategy World 2020 may be in our rearview, but now is a great time to start taking what we learned from the conference and figuring out how we can apply it throughout the rest of the year. For instance, how we can follow the trends that industry professionals are seeing in the field of analytics.

In his “Future Trends: Driving Analytics Adoption” session at MicroStrategy World, Ventana Research CEO and Chief Research Officer Mark Smith talked about analytics trends and driving adoption. Based on what we learned, here are 5 trends you can follow to maximize analytics adoption.

By 2020, 90% of business professionals and enterprise analytics say data and analytics are key to their organization’s digital transformation initiatives. – Research and Markets

Trends Driving Analytics Adoption

Using data and analytics to drive business decisions, better customer experiences, and overall digital transformation is a goal that most organizations share, but the path to adoption comes with challenges. While modern, cloud-based analytics and end-user self-service have helped increase adoption and the value of analytics, there are a few trends you can start following to bolster your success.

1. Embrace and Use Mobile Computing

Access to mobile analytics is greatly improving adoption and providing users with data immediately. Plus the widespread deployment of 5G will likely make access even faster and accelerate the mobile-first movement furthermore.

The voice and proximity on mobile provide personalized context to information. And Mobile computing with IoT and XR also provides augmented and virtual potential.

2. Embedded Analytics Everywhere

Users no longer have to switch between tools to find the data and insights they need. Instead, analytics can be integrated into a user’s day-to-day workflow. This seamless integration, enabled by Open platform, provides both internal and external users with immediate access to actionable insights inside of the applications and processes they’re already using in a context-aware manner.

3. Ensure Intelligence in Analytics

Embracing advanced, prescriptive, and predictive analytics tools is another driving force behind adoption. These tools can generate context and drive real insights. Specifically, using the Semantic model and graph to generate context and prescriptive and predictive analytics to drive real insights.

When generating context with advanced analytics, Semantic data modeling techniques are great because they can be used to define the meaning of data within the context of its interrelationships with other data. Basically, it can define how data relates to the real world. And this is key because users are more willing to see the value in analytics if insights are accompanied by context. Without context it’s difficult to take action and users are often left with more questions than answers.

Once users have context, predictive and prescriptive analytics can guide the next steps. It’s one thing to see the data, but knowing the story and suggested prescriptive action can make all the difference. Predictive analytics provides you with the raw material for making informed decisions, while prescriptive analytics provides you with data-backed decision options that you can weigh against one another.

Insights are worth a nickel, actions are worth a dollar – Mark Smith, CEO and Chief Research Officer, Ventana Research

4. Embrace NLP and Conversational Analytics

A general lack of data literacy among non-specialist users has made adopting analytics tools challenging, but improvements with natural language processing and conversational analytics are expanding the potential user pool. These tools remove the need to program queries into an analytics tool and make it easy to query databases. Conversational computing can process a large number of conversations (text and voice) at scale in the form of natural language processing and help bring immediate insights a lot more easily.

Furthermore, Gartner predicts that 50% of analytical queries will be generated via search, voice or NLP (or automatically generated) by 2020 and that NLP and conversational analytics will drive analytics and business intelligence adoption from 35% of employees up to over 50% by 2021.

5. Utilize Collaboration to Engage People

While a lack of data literacy is a challenge, so too is a lack of data democratization. Data and analytics play a key role in an organization’s success, but there’s a lot of missed opportunities if all staff members aren’t empowered to access, analyze, and act upon the information. Allowing staff companywide to inform on strategic decisions adds to the greater overall success of your business.

To empower your employees, Forbes recommends the following:

• Share the vision across the organization
• Emphasize “soft” skills
• Establish governance
• Focus on continual learning and improvement
• Develop a “data-first” approach

Takeaways for Analytics Adoption

Data and analytics tools have the power to help create or maintain a competitive edge in your industry, but the success of your data and analytics project depends on your people. Based on the five trends above, successful user adoption comes down to:

• Are your tools fast and convenient? Users are more likely to use analytics tools if they have easy access to them (mobile) and if they can find the data quickly (embedded analytics).
• Do your users have context and insight on how to take action against data? Users want quick, actionable insights that provide background information (advanced analytics) and suggested the next steps (predictive and prescriptive analytics).
• Do your analytics tools perform the heavy lifting? Users don’t want to spend an exorbitant amount of time programming queries or sorting through complex data. Allowing NLP and conversational analytics to do the hard work not only delivers insights more easily but increases the potential user pool.
• Do your users have visibility and knowledge? Democratizing data and providing all employees with visibility into data not only increases adoption, but also more informed business decisions. But granting access to data and analytics tools also requires proper training and education.

More Insights from MicroStrategy World 2020

Check out our other MicroStrategy World 2020 blog “Too Weak, Too Slow: MicroStrategy World 2020’s Big Theme.” We discuss how MicroStrategy is addressing the idea that existing enterprise applications were built for an outdated paradigm and are too weak and too slow to meet the demands of today’s users.

“Too weak. Too slow.” That’s what Norwegian chess grandmaster Magnus Carlsen, who thinks 15-20 moves ahead, says matter-of-factly to his opponents. It’s that sentiment that MicroStrategy President and CEO Michael Saylor used during his keynote at MicroStrategy World 2020 to depict traditional and outdated IT. The tech that’s been built over the last 40 years simply doesn’t cut it anymore – it’s too weak and it’s too slow.

Computers were 1,000 times weaker 40 years ago when most of the applications organizations use were developed and simply built for a different era. Saylor said those applications are “opaque, weak, and slow.” And even though technology has greatly improved, finding answers and insights is still a cumbersome process for many.

That’s where MicroStrategy’s HyperIntelligence comes in.

HyperIntelligence 2.0 at MicroStrategy World

Organizations have numerous transactional systems and the idea of either spending time and money to re-engineer them or do a “rip and replace” simply isn’t in the budget. But there’s a third option – HyperIntelligence.

MicroStrategy rolled out HyperIntelligence in 2019, but the latest release is faster, 100 times stronger, and is designed to deliver the answer before you ask the question. HyperIntelligence 2.0 provides quick, easy solutions across all your systems and allows you to take immediate action with contextual triggers.

MicroStrategy is able to deliver these types of insights through HyperCards and HyperVision.

How to use the power of the phone, the laptop to scan forward… and answer every question before I actually click. – Michael Saylor, MicroStrategy President and CEO

HyperCards

HyperCards are atomic bytes of information that can be injected into any application that’s built to be deployed on any browser (Salesforce, Excel, Outlook, etc.). They contain predefined attributes and metrics that provide an at-a-glance summary of a specific topic on a web browser or mobile device. And these cards can cover a wide variety of topics such as people, places, things, concepts, products, or processes.

HyperCards were actually introduced in 2019, but they’ve since gotten an upgrade in version 2.0. Now users can choose from 4 different card templates. There’s basic, ring, section, and matrix. Card authors can select the card template they want to use as a starting point, and then drag and drop attributes and metrics into the pre-defined drop zones. Card authors also have the ability to mix and match header styles when building a card. This gives them the freedom to combine elements from different templates and choose the header style that best fits their data and use case.

This range of card options also gives users the flexibility to create super simple cards with information that’s only needed at a glance to more advanced cards that have profile images and widgets and can be accessed via mobile devices via HyperMobile.

HyperCard improves applications you use every day

There are a lot of applications where HyperCards would be beneficial during your workday.

Email – Users don’t have to exit their email to find answers. Instead, the answers are delivered to your email platform. For example, if a colleague emails you about a product, you could hover over the product name and a HyperCard would appear with relevant information about the product such as inventory levels.

Website – HyperIntelligence uses proprietary analytics while reading a webpage as you hover over words on the page and can deliver HyperCards with information for that page.

Search – The time it takes to research an answer can be reduced from 20 minutes down to two seconds with HyperIntelligence cards.

Calendar – Users can gain information about the people invited to a meeting on your calendar. Imagine having access to relevant insights about a customer on your mobile device before your meeting begins.

HyperVision

HyperVision was rolled out in 2019 but is also seeing updates in 2020. This application allows HyperCards to be injected into Excel spreadsheets seamlessly.

During his keynote, Saylor described a scenario where a manager had a spreadsheet with 20 plus names of employees that needed to be reviewed one by one to decipher who should be promoted, who needed training, and who should be transferred.

Instead of leaving the spreadsheet to look up information about an employee, the manager could turn HyperVision on and hover over each name for the insights needed via HyperCards. And these HyperCards can be color-coded to help filter the information in the spreadsheet. This would allow the manager in the scenario described above to filter the results in the spreadsheet to only show employees who are up for promotion for example.

Intelligence is your superpower – Hugh Owens, MicroStrategy Senior Vice President, Product Marketing

MicroStrategy Cloud

So how is all of this deployed? MicroStrategy offers its cloud platform on both AWS and Azure and allows users to switch between the two or go on-premise or off-premise. Highlights of the MicroStrategy 2020 Cloud Platform are that:

• It can be piloted in a week
• It can be deployed across your entire enterprise in a month
• You can re-engineer legacy systems or spin up a HyperIntelligence environment
• It’s a low cost, low effort, and low risk

MicroStrategy World 2020 Bottom Line

MicroStrategy 2020 is smarter, stronger and faster. Deploying HyperIntelligence is an effective way to build insights into what you’re already using. Instead of re-engineering or completely replacing what you have, you can inject intelligence into the applications you use in your everyday workflow. The insights sit on top of the data you already have and HyperIntelligence makes it faster to get the answers you need.

It was exciting to see MicroStrategy 2020 presented at MicroStrategy World this year and we look forward to what 2021 brings. If you’re looking for MicroStrategy support or a partner, drop us a line or visit our MicroStrategy page.

It’s no secret that data is a massive asset when it comes to making better business decisions. But gaining the valuable insights required to make those decisions requires quality data that you can trust. And to accomplish this you need a data strategy.

Without understanding your business objectives, identifying use cases, knowing how your users access data, and much more then you put yourself in the position of making decisions based on incomplete or incorrect insights.

Next month, leaders in the data industry will meet in New York City for the Strata Data Conference September 23-26 to share insights on how to implement a strong data strategy (as well as current hot topics like AI and machine learning, which need a strong data strategy foundation to build on).

Here are four sessions to attend to learn more about the elements of a quality data strategy.

Data Strategy Sessions at Strata

Foundations for successful data projects 
1:30pm-5:00pm, Sep 24 / 1E 10
The enterprise data management space has changed dramatically in recent years, and this has led to new challenges for organizations in creating successful data practices. Presenters, Ted Malaska and Jonathan Seidman, detail guidelines and best practices from planning to implementation based on years of experience working with companies to deliver successful data projects.

Running multidisciplinary big data workloads in the cloud 
9:00am-12:30pm, Sep 24 / 1E 14
Moving to the cloud poses challenges from re architecting to data context consistency across workloads that span multiple clusters. Presenters Jason Wang, Tony Wu, and Vinithra Varadharajan explore cloud architecture and its challenges, as well as using Cloudera Altus to build data warehousing and data engineering clusters and run workloads that share metadata between them using Cloudera SDX.

It’s not you; it’s your database: How to unlock the full potential of your operational data (sponsored by MemSQL) 
10:20am-10:25am, Sep 25 / 3E
Data is now the world’s most valuable resource, with winners and losers decided every day by how well we collect, analyze, and act on data. However, most companies struggle to unlock the full value of their data, using outdated, outmoded data infrastructure. Presenter Nikita Shamgunov examines how businesses use data, the new demands on data infrastructure, and what you should expect from your tools.

The ugly truth about making analytics actionable (sponsored by SAS) 
1:15pm-1:55pm, Sep 25 / 1A 01/02
Companies today are working to adopt data-driven mind-sets, strategies, and cultures. Yet the ugly truth is many still struggle to make analytics actionable. Presenter Diana Shaw outlines a simple, powerful, and automated solution to operationalize all types of analytics at scale. You’ll learn how to put analytics into action while providing model governance and data scalability to drive real results.

Visit Perficient’s Experts in NYC

If you’re attending the Strata Data Conference don’t forget to come visit us! Perficient is proud to be a Premier Exhibitor of the event and we’ll be at booth #1338 in the expo hall. Our experts will be onsite to strategize and showcase our expertise in complex data environments, AI, machine learning, and data strategy.

You can also connect with our team to set up a meeting, even if you’re not attending the conference. We look forward to seeing you.

The Disney Data & Analytics Conference at Disney’s Coronado Springs Resort is being held in Orlando, Florida August 20-21, 2019.  This conference introduces attendees to the tools and training needed to integrate advanced decision-making techniques into business processes that center on the experience of customers, clients, and guests. One such tool that you’ll find at the conference is MicroStrategy’s HyperIntelligence.

Join MicroStrategy experts for happy hour at The Art Garden during the conference. Details and registration HERE.

Data That Finds You

This innovative zero-click analytics tool brings data to users. Instead of flipping between dashboards, web browsers, excel sheets, email, ect. to find information, you can find what you need wherever you are in your workflow. You can simply hover over a keyword in the application you’re using to gain insights.

This technology can be integrated into Office 365 applications, Salesforce, Workday, Power BI, Slack, and web pages.

How it works

A Chrome extension surfaces information from 200+ enterprise data sources and injects real-time, contextual insights directly into a user’s browser-based workflows.

Once you download the extension, HyperIntelligence scans web pages, emails, or web applications for relevant keywords. Keywords appear underlined and users can hover over these keywords to view consolidated, bite-sized views of information called HyperIntelligence cards containing real-time insights.

HyperIntelligence Highlights

• HyperIntelligence empowers experts to deploy contextual insight to any website, screen, wall, device, or application. Get answers in real time – no interruptions, no delays to your workflow and deliver insights to users within the applications they’re already using.
• “Zero-Click Analytics” is now a reality across webpages, email clients, CRM tools, productivity platforms and Office365 applications.
• Decrease the number of users that lack access to information. Insights are pervasive and accelerate decision-making with no analytical background needed.
• Receive a Single Version of the Truth – Multiple data sources are consolidated and a robust semantic layer provide a single answer across different teams and departments.

Meet the Experts: MicroStrategy + Perficient

If you’re attending the Disney Data & Analytics Conference, you’ll have several opportunities to meet with our MicroStrategy experts and learn more about how HyperIntelligence can help you gain better business insights and make better decisions. You can find us in our partner MicroStrategy’s booth #411 sharing demos and also at a co-sponsored happy hour event at The Art Garden.

Register HERE for the happy hour event.

Where:
The Art Garden
Disney’s Coronado Springs Resort
Orlando, FL

When:
Tuesday, August 20th
5:00 pm to 8:00 pm

By now, we all know that we’ll never be able to analyze the massive amount of data that continues to grow without proper tools. So we need analytics that go further than reporting what happened and help us understand why it happened. That’s why IBM has created analytics tools that instantly transform your data into relevant insights using augmented intelligence, machine learning, pattern detection, data science and more. As an award-winning IBM partner, we’re excited for the capabilities in the all-new IBM Cognos Analytics.

Cognos Analytics 11.1 Key Features

Cognos Analytics 11.1 is easy to use even for beginners, yet powerful enough for the most demanding data explorer, and can fit virtually any budget. Key Features include:

• Storytelling
• Smart exploration
• Automated visualizations
• Reusable content
• Advanced analytics

Watch the video below for more features and to hear from one of our IBM experts, Abhi Majumdar, about how he sees Cognos Analytics 11.1 helping to empower users to make smarter decisions and gain better insights.

Majumdar, Lead Consultant and Architect, is a part of the Data Solutions team with over fourteen years of technology and business consulting experience.  He enables various clients in their data and analytics endeavors and has in-depth expertise across the full IBM Analytics stack.

“I have seen a lot of solutions in the market. I haven’t seen something which is put together in one place like this.” – Abhi Majumdar, Lead Consultant, Architect – Data Solutions Group talking IBM Cognos 11.1

The cloud is enabling healthcare organizations to drive increased flexibility in maximizing the use of their data. It is also helping to lower costs, and provide better security for a variety of data types and use cases.

Organizations no longer need to set up and run a vast number of software or hardware systems on their own. Cloud services can be accessed easily anytime and anywhere, while supplementary storage volume can be added or taken away as needed.

The features and benefits of the cloud support long-term growth.

Google is one technology vendor that has its eyes set on helping the healthcare industry. Its fully managed serverless data warehouse, called BigQuery, enables companies to gain insight into their data without running a hosting infrastructure. The company says it can “process petabytes of data (even in parallel) faster than can be done on premises.”

Organizations such as Cleveland Clinic are using the cloud to make more use of their data. Beth Meese, administrative director of technology and innovations at Cleveland Clinic, said the academic medical center is using the Google Cloud’s Apigee platform to open up its EMRs and run analytics and predictive models. The goal, she said, is to make the data more actionable for clinicians.

While the cloud provides incredible efficiency benefits to healthcare organizations, analytics solutions provide the ability to dissect and present the data intelligently. Creative and detailed visualizations of the data allow stakeholders to absorb the information more quickly, as well as act on it quickly.

Healthcare organizations continue to strive for new and innovative ways of clearly communicating data, often complex, to clinicians and administrators whose valuable time needs to be focused on gaining insight, as opposed to wrangling data.

We recently published a guide that explores how data and technology can enable organizations to make informed healthcare decisions, produce better patient outcomes, and create a better patient and stakeholder experience. You can download it below.

This blog was co-authored by Tom Lennon.

During a five-week IBM training program, I learned a few things about how to sell data science models that I’d like to share it with you. The program was explicitly designed to educate and familiarize IBM’s business partners on how to expand relationships with clients; an introduction to emerging tools; and a glimpse into IBM’s future so that business partners strategically leverage clients in the competitive AI movement.

Drew Conway’s Data Science Venn Diagram

You’ve probably seen the Venn diagram with skills required to be a data scientist such as hacking skills, math & statistics, and substantive expertise. The combination of these skills are what makes a good data scientist. However, you can be a unicorn and possess all the skills and develop a phenomenal model, but the majority of your success will depend on if your model goes to production or project sponsor/ client approves it. The ability to sell your model is as crucial as the aforementioned skills.

In my experience as a data scientist, we are good at developing models, but not so good at selling these models. Sometimes, when we are presenting our models we encounter challenges: code does not run, the information is too technical, not enough material is covered, data is not available (in my experience), you can’t find your latest model, or you got off track in presenting your creation. As Murphy’s law states, anything that can go wrong, will go wrong.

So, I decided to compose a list of points on how to sell/ productionize your model.

Quick Tips for Selling Your Data Science Model

1. Know your audience

Either you are working with a data scientist, a C-level executive, or a manager. You should know who are the stakeholders and design your presentation accordingly. For example, whenever you are presenting to non-technical personnel you do not need to go into coding part of the model. If you are showing a Jupyter notebook, it is a good idea just to go through the output and hide the code, because this will only confuse and create more questions. If you have a data scientist/ technical person in the room, schedule a different meeting to go over the technical aspects of your model.

2. Engage your audience

Engaging your audience will help them stay focused on a subject through the iterative approach of asking questions throughout your presentation. For example, if you are discussing your model try to trigger their limbic system (the part of the brain concerned with instinct and mood) by asking a question about their company, or information related to the model you created.

3. Prepare a story

Storytelling is an essential part of the modeling process. I like to call this process “wow them then how them.” This excellent idea is to show your audience the results of your model and then tell them how you got there. Think of it in a way as a magic trick. First you pull the rabbit out of a hat and then you tell them how you did it. The idea is to keep your audience focused on the process of you going through the model.

4. Prepare for unexpected

Whenever you present your model within the notebook, always have PowerPoint presentation available with images from that notebook. If something doesn’t go according to plan, you will have PowerPoint as a backup.

5. Bigger than you

This tip may not apply to you; however, it is imperative.  Whenever you’re presenting a model make sure you use names that have credibility, because credibility creates a relationship. In your presentation try to use the names of the tools/ platforms that are well-known. This will help you build trust with key individuals.

6. Demand action

Start driving your discussion toward action as you present your model. Drive management to choose the next step.  Don’t assume they will get back to you, because it’s often difficult for management to see the value immediately or they’re busy. So, use your presentation and model to compel them to act.

These are my 6 points of how to sell/ productize your model. As data scientists, we all have different skills and abilities. So this list of points may not work as well for you as it worked for me. Still, I would love to hear your feedback and suggestions on possibilities or methods you encountered with presenting your model. Leave your comments below.

We are partnering with MicroStrategy for a free, one-day symposium Monday, July 23 at the Ritz Carlton in St. Louis, Missouri. The symposium will highlight the latest insights on big data, mobile app development, dashboard design, and security.

This event is a great way to:

• Familiarize yourself with MicroStrategy’s innovative analytics and mobility solutions
• Network with our team, industry experts, and like-minded peers
• Learn about MicroStrategy’s vision for the Intelligent Enterprise

Attendees will have the opportunity to attend two different instructor-led workshops. These interactive sessions are a great opportunity to either sharpen your skills or learn new ones.  The workshops will highlight data discovery and geospatial analytics.

And among several speakers, the symposium will also feature Perficient’s MicroStrategy Business Intelligence Director Steven Thompson. His breakout session, Delivering On the Promise of ‘Intelligence Everywhere’, will discuss how to provide your users with contextual analytics that are delivered in the interfaces they already use – voice, chatbots, and core operational systems.

Delivering On the Promise of ‘Intelligence Everywhere’ | 1:40pm – 2:25pm

Don’t miss this opportunity to learn best practices from global leaders and get hands-on product experience by registering for this free, one-day event today.

And while you’re here, check out our story about the MicroStrategy augmented reality app we helped create.

Enterprise data is a very valuable asset and, if used strategically, it can help drive success. One outcome of using data analytics is that you’ll be enabled with better decision making skills. Instead of basing decisions off of past experiences, you can leverage your data to understand how different choices affect your organization. Data can assist with things like everyday business management practices to thinks like mergers and acquisitions (M&A).

Enterprise Data Drives Business

Examining your organization’s metrics and aligning them with your business goals is important. In the book The Goal, author Eliyahu M. Goldratt defines three operational measurements that should be considered for successful business management:

• Throughput – Rate at which money is generated by sales
• Inventory – Money invested in purchasing things intended for sales
• Operating Expense – An ongoing cost for running a business

In addition to those three measurements, I would also add a fourth measurement to that list: Utilization. Measuring the effectiveness of resources like people, products, time, and money can be very beneficial to drive improvement. And being able to collect quality data and analyze it can help you formulate more effective outcomes in these areas.

Bottom line, every business wants to measure their success by sales, profitability and productivity while minimizing expense and inefficiency. Do this with data.

Data Builds Trust

Another way that data is impactful for enterprises is with M&A. Trust is very valuable in the context of M&A and team building for effective results. And it’s become a lot more tangible with self-service data and business intelligence tools. The ability to deliver data and analytics ad hoc to prove the effectiveness and efficiency of a business process, a product launch, a marketing campaign, or an M&A is the difference between trusting the outcome and investing more in failure to launch decisions.

In addition, the data science field takes it up a notch in providing predictive models that can proactively engage in modeling the success or failure of a product/process/service. Open Data provides the ability to use free market data for additional analysis of macro factors as well. These factors include weather, traffic, health and other critical criterion for time and money investment portfolios.

Where Are You On Your Data Journey?

Below is a Data and Analytics Maturity Continuum. It is not a model. It’s a continuous journey that iterates and improves as you move along.

Click image to enlarge.

Knowing where you are on your data journey and how to mature can be very beneficial to your organization. At Perficient we want to help you improve your Data and Analytics Strategy and improve your business processes. Reach out to one of our Data Strategy experts to get more information.

Avon, a leading beauty company, presented a customer case to our MicroStrategy partner to find a more efficient way to identify product performance in their stores. MicroStrategy, with support from our experts, took this challenge and produced an augmented reality application using the platform and augmented reality APIs. The result? An application that can display product KPIs in real-time using a tablet.

Augmented Reality App Demo

During last month’s Gartner Data & Analytics Summit in São Paulo, Brazil, Avon provided the MicroStrategy booth with a display complete with beauty products to showcase how the application works. At the booth, attendees met with MicroStrategy Director Tiago Sanchez.

Cindi Howson is a Research VP at Gartner. (Note: Perficient acquired Southport in April 2018.)

Sanchez guided attendees through the application using a tablet and the Avon products. As he raised the tablet in front of him toward a product he said, “The application instantly recognizes the image of one of our products. And now you can see all the KPIs on the screen.”

Using the MicroStrategy augmented reality dashboard you can point a tablet at one of your products and instantly see relevant product details. The dashboard is set up to show you product inventory on the left side of the screen and the sales KPIs on the right in real-time.

A tablet displaying a product’s KPIs and inventory in real-time using Perficient’s MicroStrategy augmented reality dashboard.

This application would allow customers to work more efficiently and spend more time out in their company instead of sitting behind a computer.

Sanchez said, “With this type of application you can have store operations and visual merchandising teams operating in the field using data off their products instead of operating from the back office of their company.”

Want to see what else the MicroStrategy platform is capable of? Check out our MicroStrategy partner page or drop us a line in the comments below.