Predictive Analytics Marketplaces

leverage_man_world_fulcrumEverybody knows that data velocity, volume and variety are exploding, that business expectations of transformative results for this data are incredibly high and largely unfulfilled and that the skill sets needed to leverage this data are expensive and in short supply.  It’s easy to be overwhelmed by these facts and come to the conclusion that this explosion in data is not going to deliver on its promise.

An alternative approach is to find the levers or multipliers that overcome these challenges and make these available to businesses everywhere.  This concept is central to SAP’s strategy for predictive analytics.

 Archimedes described the lever in AD 340 by saying “Give me the place to stand, and I shall move the earth.” 

We do this in a number of ways:

  1. The discipline of advanced analytics itself is the best way to extract useful information from low information density data because it mathematically identifies the valuable attributes and their relationship to the business question.
  2. We use automated techniques throughout the predictive lifecycle so that the skills and expertise of data scientists and analysts are used to maximum effect.
  3. We seek to simplify the deployment of predictive models in applications and business processes so that predictive analytics projects generate ongoing ROI.
  4. We are building predictive marketplaces to enable partners and enthusiasts to share their work in a way that makes it easy to sell and consume.

Why a Predictive Marketplace?

One of the major drivers of internet growth and success has been the growth of online marketplaces that connect buyers and sellers in an environment that allows them to do business with confidence.  From consumer giants such as eBay, Amazon, Uber and Airbnb to business marketplaces such as Ariba, online marketplaces are driving the connection economy.

We believe that predictive analytics can benefit from the same types of economies of scale that drive other online markets.  Predictive analytics is skill intensive and use-case specific.  We allow partners to build predictive extensions to solve specific use cases using their data science and industry expertise and then resell these predictive extensions to customers.  We’re investing in features which enable them to protect their intellectual property so they can monetize this investment successfully.

Our focus on making predictive analytics consumable in end-user business applications and business intelligence clients will provide them with robust deployment paths to end users.  Customers can then acquire these predictive extensions at a lower cost and risk than building the predictive models themselves.  Their data scientists can then focus on using the predictive extensions to their maximum potential and working on other problems that deliver differentiated value to their employers rather than rebuilding the wheel.

Maximize ROI with the SAP Analytics Extension Directory

The SAP Analytics Extension Directory is one of the levers that will enable enterprises to maximize the ROI from predictive analytics and Big Data.  The market is at an early stage in terms of available extensions, but we’re seeing huge interest and momentum from the partner community.  We also had eight partners who presented solutions at Sapphire 2016 based on SAP BusinessObjects Predictive Analytics.  (They were Dell, Delloitte, EY, Accenture, PWC, Qualex Consulting, d-wise and IBM).

Finally, HCP predictive services and OEM edition provide other levers for partners to take advantage of, enabling them to directly embed predictive analytics technology into their products.

If you’re interested in building predictive analytics extensions or using predictive analytics technology within your application or service, please contact Eric Fenollosa from our partner product management team.

AmickBrown.com

Why in the World should I Hire a Consultant?

Contributed by Alyanna Espina, Recruitment Manager Amick Brown

We are often asked why companies would hire outside consultants, when they could likely solve their business requirements on their own. After all, they have employees in house, which is more convenient for the company to get things going on solving their problem or starting on their new project. Not only that, these employees already know the company inside and out. Why would they waste their time bringing in an outsider and have them go through onboarding, training, and acclimating them to the culture of the company. Yes, at first look these may all seem like valid points to not hire consultants. However, there are many great reasons why companies hire consultants rather than employees.

56248327 - consult advise suggestion support consultant concept

Here are some of the reason why companies hire consultants instead of employees:

  1. They want someone with a broader perspective

Often times, companies or clients already have an idea on how to solve the problem they are facing, but they want to make sure that the solution they have in mind is legitimate. Sometimes, they may be close to the answer, but may be missing out due to being too close to the problem. So, they turn to consultants for their expertise because they may have already worked through a similar problem in the past with someone else. The consultant can also give insight on what they have seen work (and not work)  with prior clients. With this experience, they can bring new and innovative ideas, or possible challenges to the table. Consultants bring in a new frame of reference for the company, and helps get rid of the mentality of “things are always done this way” attitude in organizations. In doing so, solving problems or getting projects done on time become more effective.

2. They need more manpower temporarily

Companies have important problems that need solving, but they don’t necessarily have the employee breadth to focus on them. It makes it difficult, since the companies still have to focus on their everyday operations and new projects usually require reprioritizing employees’ core job responsibilities. However, hiring new employees to fill in these gaps may not always work out considering most of these projects do not last very long or may not happen at all. Despite, having employees in house, companies might have difficulties getting the teams organized to do this critical work.

In these situations, consultants come in to serve as temporary, highly skilled employees. Since, they are not full-time employees of the company, it is often cheaper to use consultants than to hire new employees. Consultants are used to switching around companies, creating a very fast learning curve. Also, companies do not have to take their own employees away from their actual day-to-day jobs. It’s a win-win situation all around!

3. They need specific skills that they do not currently have

Another reason why companies hire consultants is to acquire specific skill set that might not be easily available in house. Working with firms who have access to these highly skilled professionals may be more efficient for your company.  With constant innovation in the tech world, keeping your staff 100% state-of-the-art is nearly impossible. Luckily, consultants make it possible for companies to bring in the skill set they demand whenever they need it, since staffing firms make it their business to keep consultants trained and ready for every situation.

4. Sometimes, it is better to have a mediator/ nonpartisan influence

When companies run into a challenging problem, it can be troublesome for them to make decisions or take the necessary actions without getting caught up in emotions or politics. In order to alleviate the situation, companies bring in consultants to provide unbiased solutions to the problem. Consultants are then able to come in and ensure that the problem is being handled by an external party that is both experienced and removed from any controversies. Moreover, consultants can also serve as back-up or affirmation for a client who is attempting to carry out a new idea that might not be well-received within an organization, without any risk to their career.

 

There are many, many more reasons why companies hire consultants/contractors. I have only touched on a few and would love to hear your must unique reason for hiring a contractor !

With the advent of culture matching and executive oversight for every project, the reward will outweigh the risk.  Save the high dollar value of advertising, screening, interviewing, and hiring an employee by meeting requirements with consultants.

AmickBrown.com

Part 1: Winning your End Users – SAP BusinessObjects Design Studio or SAP BusinessObjects Lumira or …

 by Iver van de Zand,  Guest Blogger

 

confused_lost_man_cartoonBeing part of one of the leading software companies is great and brings advantages and (sometimes) disadvantages. A key element I like so much in my work is that with my company I can be part of large—or even huge—scaled analytics journeys with customers and BI competence centers who need to serve thousands and thousands of users. In today’s digital economy, they all struggle similar challenges. Let us focus on the business users and reflect their biggest requirements for analytics, and how this often brings us to the self-service dilemma.

Enterprise End Users Require at Least:

  • Self-service capabilities: Business users require a great deal of autonomy in their analytics work. They want to easily create, deploy and share their business analytics content themselves without being too reliant on their ICT or BI Competence Centers. The data analysts among them even require access to non-corporate data in order to blend this with the corporate data and search for new insights.
  • Agility and Flexibility: It’s almost become a magical word, ‘agility’ is what I hear every user talking about. Users nowadays require full-flavor flexibility when using analytics. It means easy accessible on any device, the ability to change graph types on the fly. It also means being able to swap measures and attributes at any place in the analytics dashboard, storyboard, or report. Users also require drill-anywhere capabilities and a definite must-have is to drill to the transactional level if applicable. The agility requirements for tooling are based on what the business decision makers’ need to have towards process or market fluctuations and their customer needs
  • financial dashboardOnline or real-time information, yet still highly performant. As you already expected, all the users I met want the data to be accessible in real-time and—ideally—also online. I understand that need; driven by this agility, users absolutely need to have the latest data to respond to any fluctuation in process or market.
  • Consistency in metrics and metadata: Though this should be a no-brainer, users frequently mention that they’ve had negative experiences in the past with consistency in metrics and metadata. In any type of business analytics applications (reports, storyboard, workspaces or dashboards) they expect consistency in metrics, the use of definitions, hierarchies, prompts variables or other metadata-related content. End of the line!
  • Governed: Oh yes, end users do have concerns about governance. Though everybody always wants to have access to anything, deep in their hearts they all understand authorizations and security are top notch subjects and need to be treated with ultimate care. Another one here is SSO (Single Sign On)—would you like to logon and enter your credentials 75 times per day? Nah, don’t think so, so SSO is a must-have.
  • Visually appealing: Basically, I’m talking about the user experience here. Since analytics are widely spread—often also to my customer’s customers—they need to be visually appealing to attract the attention. This element of visually-appealing analytics is more complex than you might think. The visualizations need to have the creativity, effect, and structure to exactly communicate the message that “needs to be communicated.”(This subject is worthy of a few articles already.)

The Self-Service Dilemma – SAP BusinessObjects Lumira or SAP BusinessObjects Design Studio?

train_schedules_infographicSo, here we are with the large enterprise using SAP BusinessObjects Business Intelligence suite and users are looking for self-service and agility. Typically now the self-service dilemma starts: users, architects, and IT leaders are all very well informed these days, and consider SAP BusinessObjects Lumira as the ultimate tool to provide for every end user.

And they have a point, considering end users get full flexibility and self-service capabilities while the learning curve is extremely low. It brings powerful visualization capabilities and people can easily blend their data with other – i.e. external – data. (See a detailed component selection tool.)

But  I tend to challenge their considerations, especially if SAP Business Warehouse and/or SAP HANA are involved. They forget about SAP BusinessObjects Design Studio for enterprise dash boarding, and I don’t know why. Apparently, they still believe SAP BusinessObjects Design Studio is a developer tool and that is permanently incorrect.

In a lot of cases, SAP BusinessObjects Design Studio can cover all the end-user needs mentioned above, and it does this in a remarkably powerful way. SAP BusinessObjects Lumira really comes in for data analysts. It is a matter of clearly choosing the best-suited BI component to sort out the self-service dilemma enterprises might have.

I’ll go into detail on how to choose in my blog post next week. Stay tuned!

AmickBrown.com

The Nature of Supply Chain Risk

Contributed by Matthew Liotine, PHD

In our last article, we looked at the magnitude of the supply chain risk problem and how it is a major concern for most companies – large or small. Studies have shown that most companies experience one or few supply chain disruptions annually, each resulting in some significant loss. Many of these disruptions involve key suppliers or those below Tier 1. Never the less, many firms still lack commitment to controlling supply chain risk for the reasons of the costs and complexity involved. Consequently, many firms will tend to favor short term ROI solutions versus longer-term solutions that involve investing capital to improve both their supply chain infrastructure and operational resilience. Larger firms will manage risk more strategically using a combination of executive governance and/or data driven approaches. While operational data is increasingly becoming more available, much work is still needed in leveraging such data for strategic risk management. The nature of risk in the supply chain lies with a firm’s exposure to potential disturbances to the supply chain operation. Many of these disturbances can be manifested in various ways, usually in the form of single, multiple or recurring events, conditions or phenomena. In this article, we will examine what kinds of hazards, events or triggers can possibly compromise supply chain weaknesses and can ultimately threaten supply chain operations.

The Changing Nature of Threats

When one thinks about threats to a supply chain, natural disasters usually first come to mind. Figure 1 shows the trend in major U.S. disaster declarations as reported from the Federal Emergency Management Administration (FEMA, 2011). While it is clear that there has been a rising trend in declarations, the reasons may vary from the increase in severe weather events due to climate change, to political influences. Figure 2 shows a trend in worldwide natural catastrophes (Munich RE, 2014).

SC chart 1

Figure 1 – Trend in U.S. Disaster Declarations

SC chart 2

Figure 2 – Trend in Worldwide Natural Catastrophic Losses

As evident in the Figure, there’s an ever growing trend in measured losses. While natural catastrophes have been occurring since the beginning of time, their effects over the years have been more far reaching due to population growth and insurability trends. These trends, combined with human created disruptions, together have created an environment of increased volatility for supply chains, as depicted in Figure 3 (Martin & Howleg, 2011).

SC Chart 3

Figure 3 – Trend in Supply Chain Volatility

This Figure shows the annual volatility in a composite set of key business parameters such as exchange rates, interest rates, shipping costs and raw material prices. They are combined into a single volatility index using the coefficient of variation (CoV) of the business indices representing these parameters to produce a normalized volatility metric. While in the far past there has been a timely return to supply chain stability following adverse events, the recent increase in volatility bandwidth questions whether this trend would likely continue. The high collective swings (versus individual swings) in key business parameters, which may be correlated with each other, suggests that an alternative approach to designing supply chains and managing supply chain risk might be preferred.

Volatility can arise from many possible undesirable hazards, conditions or trigger events. The likelihood of such events compromising a supply chain’s vulnerability is regarded as a threat. Table 1 lists categories of possible threat sources and examples within each category. The list was compiled from several studies and is not meant to be all-inclusive (Tummala & Schoenherr, 2011) (World Economic Forum, 2012) (Accenture and World Economic Forum, 2013) (Chopra & Sodhi, 2004).

 

Table 1 – Supply Chain Threat Sources

Disruptions

  • Natural disasters
  • Terrorism and wars
  • Labor disputes/shortage
  • Single source of supply
  • Insufficient supplier capacity or responsive
  • Extreme Weather

Capacity

  • Capacity inflexibility
  • Capacity cost increase
  • Geographical concentration
  • Insufficient capacity

Information System

  • Over-reliance on systems
  • Information infrastructure outages
  • Insufficient system/network integration
  • Incompatible IT platforms
  • Unavailable data/information
  • Inaccurate data/information

Sovereign Regional instability

  • Conflict & political unrest
  • Government regulations
  • Loss of control
  • Intellectual property breaches
  • Corruption
  • Export/import restrictions
  • Illicit trade & organized crime
  • Ownership/investment restrictions

Strategy & Operations

  • Lean processes
Demand/Customer

  • Frequent changes in demand
  • Sudden unforeseen demand surges/dips

Process Design changes

  • Communication gaps
  • Inaccurate specifications
  • Supplier non-compliance

Procurement Unqualified supplier

  • Inflexibility of supplier
  • Poor supplier quality or process yield
  • Supplier insolvency
  • Rate of exchange
  • Flawed supplier’s sourcing
  • Commodity price volatility
  • Global energy shortages
  • Lack of supplier transparency

Transportation Paperwork and scheduling

  • Strikes
  • Port capacity/congestion
  • Higher costs of transportation
  • Piracy
  • Infrastructure failures
  • Excessive handling
  • Custom clearances at ports
  • Border delays
  • Transportation breakdowns

Structural Fragmentation along the supply chain

  • Extensive subcontracting
  • Dependency on a single source of supply
  • Extensive outsourcing
  • Extensive offshoring
  • Product/supply network complexity

 

 

The Changing Course in Risk Management

Many supply chains are designed under the assumption of operating in stable environment (Martin C. H., 2011). While approaches such as Just-in-Time (JIT) and product-focused production are designed to minimize variation, maximize efficiency and ultimately reduce costs, they require a more rigid command-control management strategy which may not necessarily respond well in a volatile environment. In addition, the effects of volatility can be further amplified in a rigid supply chain that lacks resiliency. Building supply chain resiliency may counter the notion of an efficient operation, since it requires the addition and re-allocation of capacity, inventory and other resources that could serve as shock absorbers to withstand disruption. Since these controls will entail added costs, the use of a risk analysis methodology would be an effective tool in helping firms identify, evaluate and prioritize the most cost-effective risk-control options. It was clearly evident in Table 1 that there can be numerous sources of threats to a supply chain. However, since many threats can have similar outcomes on a supply chain operation, control options can be devised using an “all hazards” philosophy, which entails implementing controls to minimize the common effects of multiple threats or threat categories.

Conclusions

Supply chain disruptions can arise from many sources, both natural and man-made. Current trends indicate a continued rise in measured losses from natural events and increased business volatility in response to man-made events. Traditional supply chain structures designed for operational efficiency may not necessarily be able to withstand disruptions arising from numerous threat sources. Creating a more resilient supply chain may require the use of risk assessment tools and methods to help decision-makers identify the most cost effective controls that could minimize the common effects arising from multiple threats. In the next article, we will examine some common supply chain vulnerabilities and their ensuing risks.

Bibliography

Accenture and World Economic Forum. (2013). Building Resilience in Supply Chains. Accenture.

Chopra, S., & Sodhi, M. S. (2004). Managing Risk To Avoid Supply-Chain Breakdown. MIT Sloan Management Review, 46(1), 53-61.

FEMA. (2011). Democratic Blog News. Retrieved from http://www.demblognews.com/2011/09/water-development-board-report-says.html

Martin, C. H. (2011). Supply Chain 2.0: Managing Supply Chains in the Era of Turbulence. International Journal of Physical Distribution & Logistics Management, 41(1), 63-82.

Martin, C., & Howleg, M. (2011). Supply Chain 2.0: Managing Supply Chains in the Era of Turbulence. International Journal of Physical Distribution & Logistics Management, 41(1), 63-82.

Munich RE. (2014, January). Topics Geo: After the Floods. Munchen: Munich RE.

Tummala, R., & Schoenherr, T. (2011). Assessing and Managing Rrisks Using the Supply Chain Risk Management Process (SCRMP). Supply Chain Management: An International Journal, 16(6), 474–483.

World Economic Forum. (2012). New Models for Addressing Supply Chain and Transport Risk. World Economic Forum.

Integrate Non-SAP Data into Planning

Contributed by Gunnar Steindorsson, Allevo US

Earlier we took a look at how effective cost planning in SAP isn’t always easy – but how it can be with Allevo.

Let’s take a deeper look at one challenge specifically that Allevo accomplishes with ease:  integrating data from systems or processes outside of SAP.

As you know, it’s not easy to bring data into SAP from other systems – say production or sales plans – and integrate these into your planning process. Allevo’s innovative Satellite Technology was designed to do just that however.

With Allevo, data integration with external systems occurs automatically and in real-time. Best of all, once your planning is complete you can save the results in SAP along with your assumptions, comments and other metadata for later retrieval and reference.

Allevo integrated non sap data chart

Better yet, with Allevo you work in your familiar, easy-to-use Excel environment, using your own templates, all while fully integrated with SAP.

So, if you’re tired of not having real-time access to your vital planning data, frustrated by cumbersome workarounds, and annoyed with working in a system that doesn’t support the way you want to work, Allevo is your solid answer.

Contact info is below.

amickbrown.com.allevo

 

 

Why SAP HANA and Spark for Big Data Predictive Analytics

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By David Jonker,

Sr Director SAP Big Data Product Marketing, Technology & Innovation Platform

Big Data offers analysts and data scientists the opportunity to build more sophisticated and more accurate predictive models than before, but without the right data environment, it’s not easy. It requires an in-memory architecture that supports thousands of columns and billions of rows and a predictive analytics tool that can harness that architecture, such as SAP BusinessObjects Predictive Analytics.

Twentieth century technology is insufficient. Blame it on the disk. Back in the 1980s, database engineers saw a world where memory was extremely expensive. Just one terabyte of RAM cost over $100 million US dollars. Today, we can get it for less than $5,000 US dollars. So, vendors built database architectures centered on the disk.

In a Big Data world, the disk is simply too slow. Consider this: reading 1 petabyte of data off a disk sequentially – i.e. no seeking, just end-to-end straight off the disk – takes 58 days using the fastest hard disk available today (according to the Tom’s Hardware website). SSD definitely speeds things up: two days with the fastest SSD RAID. It’ll cost millions to buy, though.

In many ways, Big Data is a real-time data access problem. That’s precisely why innovators are developing new ways to store and process data, all in an effort to get around the hard disk bottleneck. All of the approaches, in essence, minimize the bottleneck in order to improve response time.

Distributed Computing

Distributed computing spreads a lot of data across many disks that can all be read simultaneously. Hadoop builds on the concept of distributed computing, but opens up the platform to handle any data set with any arbitrarily designed algorithm. To overcome the disk, the Hadoop community built Apache Spark, which provides a distributed data processing architecture, like Hadoop HDFS, that operates in-memory across commodity hardware.

Columnar Databases

Like distributed databases and Hadoop, columnar databases optimize data storage architecture in order to reduce the amount of data read off any one disk. It does this by grouping related attributes, or columns, together. The assumption is that most analytical queries only use a subset of columns, so you should only access data related to those specific columns. They also highly compress the data, further reducing the number of bits read off disk.

In-Memory Databases

In-memory databases take it to a whole new level by removing the disk from the equation altogether. It leverages the power of today’s processors to read and analyze data at a raw speed that’s 1,000 to 10,000 times faster than reading data off the disk. In some cases, customers have experienced performance gains of 100,000 times faster. How?

–   Compress the data with in-memory columnar data stores

–   Move the data accessed most often into L1 caches on the chip

That’s why we are so bullish about in-memory and the SAP HANA platform for Big Data. That’s not to say disk solutions don’t have a role to play. But…at the core you want an in-memory system that can run algorithms where your data is. No moving the data to the algorithms, that doesn’t work in a Big Data world. Instead, move the core algorithms into the data system.

SAP BusinessObjects Predictive Analytics

SAP BusinessObjects Predictive Analytics is the right tool for business analysts and data scientists to build predictive models from Big Data. First and foremost, it can analyze data inside SAP HANA and Apache Spark. There’s no need to transfer data out of these environments for processing. Rather, the SAP BusinessObjects Predictive Analytics processing engine can run inside these tools –  dramatically improving performance.

SAP BusinessObjects Predictive Analytics is also able to analyze exceptionally wide datasets. In fact, you can have up 15,000 columns in a dataset, while other tools support only a few hundred to 1,000 columns at most. This ensures that your predictive models provide the greatest level of accuracy possible.

Big Data is radically altering our world. It’s a game changer. For those who grab hold of it, you have an opportunity to propel your business forward – and the surest way forward is with SAP BusinessObjects Predictive Analytics running on SAP HANA or Apache Spark. It’s is the best combination for building predictive models on Big Data, whether you’re a business analyst or data scientist.

Read Unleash the Power of Predictive Analytics with the SAP HANA Platform to learn more.

AmickBrown.com  for Data,  HANA,  Analytics, and Reporting

Diversity – Embracing the New View

By Karen Gildea, Managing Partner, Amick Brown

We live, play and work in an immensely diverse world.  To classify ourselves, we align with others of the same representative group.  We categorize ourselves into numerous different groups based on race, gender, age, religion, culture, ethnic background, etc.  The list of identity groupings can be endless.

The traditional view of diversity in the corporate world has had a focus on preventing discrimination of specific minority groups – preventing exclusion.  We are experiencing a shift now….from preventing exclusion to embracing inclusion.  We are moving away from regarding diversity only as a compliance requirement, to recognizing the value of and benefiting from the various perspectives of different identify groups as a business strategy.

The new view of diversity as defined by the Society for Human Resource Management encompasses “the qualities, life experiences, personalities, education, skills, competencies and collaboration of the many different types of people who are necessary to propel an organization to success.” 

20633211 - diversity color tree finger prints illustration background set. file layered for easy manipulation and custom coloring.

Some of the benefits associated with a focus on diversity and inclusion include:

  • Diverse teams that include individuals of different ages and with different backgrounds and perspectives can be more creative and innovative because the contribution and influence is more varied and therefore rich.
  • Employers want the best and brightest to join their organization. You don’t know what identity group your best match might be associated with.  A company with strong diversity and inclusion goals and a diverse workforce will be attractive to high potential candidates regardless of their identity group.
  • As with employees, customers will be associated with many identity groups as well. A diverse and inclusive workforce as well as a brand that represents a company’s diversity position will be helpful in attracting those customers.
  • While affirmative action programs still exist to counter-balance historic discrimination, fostering a diverse workforce, and working with diversity supplies will satisfy compliance requirements – not doing so might result in missed opportunities.

At a high level, developing a business strategy to support diversity and inclusion can be approached in a similar fashion as other business strategies.

  • Must have Executive commitment;
  • Create a responsible party/organization to champion the effort and shepherd its development and progress;
  • Perform an assessment of the current state that includes not only the demographics of the organization but also the perspectives of the employees regarding the company’s diversity;
  • Evaluate the results of the assessment and determine path forward that might include hiring goals encompassing all of the dimensions of diversity, diversity supplier purchasing goals and organization leadership goals to name just a few;
  • Facilitate organizational, process and any system changes required to support the strategy and goals;
  • Communicate and provide training to all in the organization. Ensure the message is shared by the executive leadership to demonstrate its commitment to diversity;
  • Monitor, measure and evaluate – adjust as needed over time.

Consider diversity in terms of the benefits it can bring to an organization.  Companies that expand their hiring practices to include individuals from varying backgrounds and those just entering the workforce in addition to those that are seasoned with experience will be rewarded with a rich and diverse workforce.  The brand will benefit as well, and at a minimum, the daily work life will be enriched by the many cultures, generations and viewpoints offered by a diverse group of individuals.

As a core belief in how we approach our business , Amick Brown works hard every day to promote the internal and client-facing benefits of diversity.