If the right people do not have the data they need, how can the intelligence be accurate?

By Ashith Bolar ,  Partner and Director AmBr Data Labs

Lack of user-acceptance is considered a failure of any new Information System — a rule that equally applies to a Business Intelligence initiative. And the astounding fact is that this is a very common occurrence. The reasons can be varied, such as the quality of data, the usefulness of the analytics provided by the system, or merely the user-interface being unfriendly.

However, what is not considered in assessing the success or failure of the system is the number of users who did not get access the system — an error of omission (pun intended). Typical IT projects finalize the initial set of end-users right at the inception of the project, and no later than the requirements phase. To manage the scope of the project, it is typical to keep a small and manageable initial user-base. However, I believe that this is a mistake!

I believe it is a mistake, that in trying to ensure the success of the project, the scope of the BI deployment should be restricted to a few. The true value of a BI enterprise is the crowd-sourced intelligence that you derive from it — and by this assertion: the more the merrier! Not only will a wider audience give us a better assessment of the success of our BI initiative, it will also ensure wider and quicker post-deployment enhancements.

Starting with a large audience of users has many challenges, least of which is managing the scope of the BI project. Given that a data warehouse typically contains sensitive data, one of the main concerns of a large user-base is data security — ensuring that only the right users get access to the right data. This concern leads to the usual decision of limiting the initial user-base to just the power-users, ones that require none or minimal data security.

pocker chips and aces

We see your challenge and raise you AccessOne©!

AccessOne is an information security software specifically designed for SAP™ Business Warehouse (SAP-BW). AccessOne allows you to build your access-control security in an easy excel-like matrix, and deploy it with a few clicks.  AccessOne can extract access information from your ECC system (be it role-based, structural authorizations, etc) or a traditional SoD ACL matrix, or even an excel file you created on your desktop. 

So that you can visualize AccessOne more completely–

A BI solution’s data security implementation is quite different from an OLTP system, even though they both try to achieve the same goal by means of a same set of parameters. The OLAP authorization mechanism works in the reverse direction of the procedures employed by an OLTP system.

See schematic below:

Take an example of an OLTP HR system / employee database. Here’s the sequence of events that occur when a user interacts with the system:

A1 1

Now consider its BI counterpart. The typical user request sequence goes something like this:

A1 2

Although, this is a simplified view, it’s easy to visualize the change in the mechanics of how authorization works between an OLTP and an OLAP system.

The power of AccessOne is in its ability to transform security parameters from the data structures that are designed for an OLTP system to the ones that are more suitable for an OLAP system. Moreover, AccessOne applies these authorization checks to any and all users of the SAP BI system. It will replicate your OLTP (ECC) system access parameters (role-based, structural, etc) into OLAP (SAP BW) system access parameters (analysis authorization). 

With this power, and with the guarantee that your BI system access is exactly the same as your ECC, you can now open up your BI system to all the ECC system users, be it power users, domain-specific users, supervisors, or individual-contributors.

Another power of AccessOne is “overriding” or “overloading” authorizations derived from OLTP. With a single access-control entry, you can override or overload (add to) the access of any user or user-group. For instance, if you have an end-user with limited access in the Finance ECC system, however you want to provide this user with extended access to the BW system on the finance cubes, this can be achieved by inserting a single access-control entry in the BI system.

In the following blog posts, we will examine some complicated yet typical case-studies to illustrate the power of AccessOne.

– Watch this Space –



25 years into a career and you are Outsourced – time to Panic or a Gift?

By Karen Gildea, Co-founder and Managing Partner
Amick Brown

Karen Gildea

Like so many of my peers, and by that I mean those that
started their careers years ago with the plan to remain at the same company until retirement, the news that outsourcing will end your career there is shocking to say the least.  When you must leave your company for whatever reason, and you aren’t really ready or old enough for retirement, it is quite distressing.  You look at the many millennials who seem to so comfortably pick up and move to a new company when they see a new opportunity and you think, “what do I know and what skills do I have that would enable me to start again somewhere?”

What felt like the worst thing that could happen to my career…….WASN’T.

I spent more than 25 years working at a company that was so large that there was an endless amount of potential in terms of jobs, career paths and the ability to climb the corporate ladder.  I loved my job as it was constantly changing and enabling me to grow.  I loved the people I worked with and through the years they became a kind of extended family.  This was my world – I never looked beyond it.

As I started to think about the situation at hand, some truths were evident. Through the years, I was afforded some very valuable training and experience.  I managed a team that was responsible for building and supporting 24 x 7 applications for a user base that numbered in the hundreds of thousands.  We learned, sometimes the hard way, that the right people, constant communication, process, documentation, and a strong focus on quality assurance and system performance are required for success.  When you are there not only to implement systems, but to support them, you learn to be very thoughtful about design, testing and user communication and training.  These are sometimes areas that are of little interest to those who implement and move on.  We had a roadmap and a long term view of the solutions we were building and we had a lot of experience that would ensure our success in getting there – but that was over.

Make a Plan, Work the Plan, Be Accountable

Together with some of my colleagues, we decided to start a small consulting business.  We realized that the skills and experience that we had acquired building and supporting SAP and BI solutions for such a large implementation would be of value somewhere.  We believed we could make this work….but at the same time we definitely had moments of concern.  We met and planned in our dining rooms.  We understood from our long-term and collective experience the value of developing a detailed project plan, holding people accountable, and then working the plan.

As Amick Brown became a reality, we knew we had the expertise in SAP and Business Intelligence, but what about running a business?  We had a lot to learn, but it turns out that there is a lot of help out there.

First, we found a mentor. This person had already done what we were trying to do.  Her business was in another state with a different focus so competition was not an issue.  She was a huge asset and we will be forever grateful.  We asked her endless questions, took copious notes and still reach out to her from time to time for advice.

We then took advantage of all of the resources we could identify.  The Small Business Administration provides immeasurable support to small businesses. Through the SBA, we connected with the Small Business Development Centers (SBDCs) in the three counties in our area.  The centers are there to provide training, counseling and support to small businesses.  We attended all of the training that we could about starting a business, marketing, payroll, legal issues, accounting, etc.  We also discovered the Procurement Technical Assistance Center (PTAC) which is another valuable resource that has a focus on government contracting.  We attended many PTAC training sessions where we learned about doing business with the various government agencies and responding to Requests for Proposals.  Most of the training we attended was free and when there was a cost, it was minimal.

We worked with our bank to obtain an SBA backed loan to support our start-up costs.  I can’t stress enough the value of a good banking relationship.  I have to give a shout out to Wells Fargo for being such a good business partner and providing such terrific support through the years.


We pursued all of the certifications that were appropriate for us. We are a woman-owned business, we are a minority-owned business and we are a small business.  It is a lot of work to complete each application and it may be a bit overwhelming as you begin the process, but it is well worth the time.  Doors will be opened instead of closed because you are a supplier that holds a specific certification.

Conferences and business matchmaking events are one of the best places to learn and make connections.  We connected with people in other companies and government agencies, and identified additional useful resources to call upon when needed.  Each event helped us learn, grow and refine our marketing material and “elevator speech”.

Our first contracts were with companies we connected with through our already extensive network.  Though they were small contracts at first, it provided us the opportunity to build up our support systems that included HR and payroll services, legal support, accounting processes, web support and recruiting systems and processes.  Obviously, we grew very quickly beyond SAP Business Intelligence – a greater reach for our growing customer base.

panic buttongift icon

So, was outsourcing a panic situation or a gift? Here are the lessons learned:

  • Starting a business is completely possible. We found support everywhere we looked and people wanting to see us succeed.  We started with what we knew, and then looked for help and guidance for what we didn’t know.  Help is out there.
  • Relationships are everything – We understand that without good relationships with our clients, our employees, our subcontractors and our other business partners we won’t thrive. We will always do right by each of them.  They can count on us.
  • Continue to think long term – We make sure that we hire seasoned people who understand the long term impact of design, and in the event one of our hires needs additional assistance to ensure success we make sure it is provided. The long term success of our clients and the relationship we have with them is of utmost importance to us.
  • Be frugal – We have always had an eye on cost containment and we don’t spend money on things that don’t bring value. We are fairly modest with business purchases and we would rather offer better compensation and benefits packages to our employees and contractors – this way everybody wins.
  • Being a business owner is a completely rewarding and exciting experience. We have a renewed energy and enthusiasm toward all that we do.  We learn something new every day and life is good.

To date we have made the San Francisco Business Times Fast 100 list which lists the fastest growing privately held companies in the San Francisco Bay Area two years in a row and the Largest Women-Owned Business list three years in a row.  Our US focus is growing markets in the East and Central United States, as well as the West.  Our detailed plans, working them carefully, and staying accountable are making a new business success our reality.

Keep an eye on Amick Brown.  Good things are happening here!

2016 and Business Analytics: Be Prepared for a Smashing Year: Part One

by Iver van de Zand, SAP

The end of the year is always a time to reflect, but also a time to look ahead and think about what might be different or innovating next year.three-spheres

Reflecting on 2015, three things immediately come to mind:

  1. Interactive self-service business intelligence (BI) has definitely landed and earned its permanent place. Every top-100 customer I talked to has self-service business intelligence in its BI strategy plans.
  2. “Traditional” business analytics (as in managed reporting and dash boarding) is not sufficient anymore for full performance management. A closed loop portfolio of analytical, predictive, planning, and GRC information is becoming a necessity in today’s management of processes and business flows.
  3. The value of in-memory platforms is now being recognized by leading companies. They massively adopt in-memory platforms to not only run their core applications, but also to integrate business data and facilitate analytics.

Looking forward, I’m sure you’ll agree with me that analytics is heavily influenced by the readiness of organizations to adapt to change resulting from the Digital Transformation. Connected economies and networks, data that’s available at any moment at any level, and sensor techniques allowing for new business models—they all heavily influence our needs for insights. As such, they heavily influence the 2016 trends for business analytics.

Did Tableau Lose Its Head?

Recently, I did the Google search exercise for “BI Trends 2016″and was both shocked and amazed. Our friends from Tableau’s marketing department have succeeded in monopolizing  80% of the first 20 hits! However, if you read closely, you’ll notice they are all referring to the exact same article. (Though they all seem to be different articles, they all cover identical things.)

I was further shocked  by the lack of insights these identical articles cover.  My feeling is that the articles point out  BI trends for 2014 (or earlier). “Governance and self-service become best friends,” it says. Dear people from Tableau, self-service BI can only exist by the sake of data governance. If self-service BI is not governed properly, there is no sense for it. And the trend mentioned as “Data Integration gets Exciting”? This was something everybody focused upon in 2012.

Analytical Projections for 2016

So what can we expect for 2016? Personally, I can only reflect on what I see and hear when talking analytics with key customers every single day. For me, these discussions have provided food for thought. Listening to the plans that my customers have, I can extract five key trends for business analytics in 2016:

  1. Self-service BI will become a commodity
  2. Business will embrace the portfolio loop
  3. Companies will really analyze Big Data
  4. Cloud BI adoption will accelerate
  5. Operational BI footprint will grow

Let’s take a closer look at the first two trends in today’s blog.

  1. Self-Service BI Becomes Commodity

Governed self-service BI will further find its way to all echelons of organizations. And the reason is simple— business users finally have the opportunity to drive analytics in their organizations. While 2015 was the year of adopting self-service BI, 2016 will be the year of the massive roll-out. Self-service BI is becoming a commodity in 2016 with the number of business users growing rapidly. From a functional perspective, the success of self-service BI is greatly determined by its ability to:

●  Interact with the user. Self-service BI can be adopted quickly because end users are able to interact with massive amounts of structured and unstructured sources of information.

●  Make data and insights easily visible. Business users really recognize the value of making insights visible. The simple but clever idea of using visualizations and analyses to create your own stories (storytelling and infographics) is very successful. Nice examples are GEO-driven stories, dashboards , and D3 open- source visualizations. These, combined  with interactivity, make self-service BI a stunning combo. As I’ve mentioned before,  “our meetings will never be the same.” We can now use interactive, visualized insights to discuss and monitor the heartbeat of our company in real time!

●  Be agile with new and ever-changing data. A third success factor (what’s in a name J) to self-service BI is its agility. This agility is a huge value-add because it allows business users to really simply acquire and enrich new data and use it for analyses. Bear in mind, this also applies to Big Data using in-memory computing.

  1. Business Embraces the Portfolio LoopReal-time business wheel

I’ve made my point on the importance of the closed loop portfolio in earlier blogs. Every key customer I met last year who’s willing to embrace Digital Transformation is seeking an integrated and governed platform to analyze, plan, predict, and assess risks in a constant and permanent loop.

I use the word ‘integrated’ on purpose here, since here is where the difference is made—customers seek to have real-time integration between their business analytics, their detailed planning, and the predictive models that affect, for example, product mix or pricing strategy. The integration also needs to be on operational financials and towards risks and compliancy cases when needed.

Many of my customers have accomplished this on a near-integrated level that isn’t real time by using individual components that access each other’s data. Products like SAP Cloud for Analytics are revolutionary here since they provide the closed loop portfolio covering real-time, interactive integration on all mentioned areas. Markets have been waiting for this for quite some time and are eager to adopt. It allows them to interact with market fluctuations that speed up due to the Digital Transformation. You can look at the examples I described in a previous blog for the retailing sector to understand the scope of the closed loop portfolio.

Stay tuned for my next blog. I’ll discuss the other three trends I see for business analytics in 2016: analyzing Big Data, the acceleration of cloud BI, and  the growth of operational BI.

Follow me on Twitter @IverVandeZand.

Amick Brown is here for you.


The Real Business Intelligence

Ashith Bolar, Director of Research, Amick Brown

In the state of the art of computing, every company generates a large amount of data, and it goes without saying that every organization does some sort of data analysis on this data. Big and small companies invest in Business Intelligence in some shape or form. The ubiquity of big data infrastructures, such as those from SAP, as well as Hadoop and its various distributions also has enabled even smaller and medium sized businesses (SMB) to perform data analytics at scale.

glass wall meeting

Loosely speaking, Business Intelligence (BI) is a set of techniques and tools used to transform raw data into meaningful and actionable information. However, simply based on that definition, virtually every exercise in data analytics can be considered as Business Intelligence. The true value of a BI is only realized when the latest tools and technologies are applied in order to determine the historic, current and predictive views of the business.

One of the applications of BI is Predictive Analytics (PA). PA encompasses a large and fluid set of tools based on statistical and mathematical techniques to analyze historical data and subsequently build predictive models. The idea is that historical data contains patterns that, if recognized and correctly applied, can be used in predicting the future. This enables a company to predict and proactively respond to the future state of the business, say customer behavior, market conditions, etc.

growth graph

Take a look at your current BI system. Are you only analyzing  historical data, and at best enumerating the current state of your business? Or does your Business Intelligence platform help you model the future and enable you to predict the course of your business? Are you able to identify risks and opportunities well before they occur?

PA captures patterns and relationships among the various factors in your business, giving you a deeper perspective of risks or potentials associated with your current course of business. This enables you to make optimal changes to your business in order to make the most of the current and future market conditions.

Current technology offers very cost-effective means of Predictive Analytics that SMBs could implement with virtually no upfront cost.  SAP’s Predictive Analytics Software gives you a robust set of tools in this space. These tools run on your enterprise data and any supplementary data that you provide.

SAP’s Predictive Analytics Library (SAP-PAL) provides the following list of capabilities:

  • Predictive Modeling : automated set of tools to build predictive models
  • Predictive Scoring : identify and evaluate relevant variables in predicting
  • Predictive Model Management : enable end-users with limited knowledge of the science of predictive analytics to ask what-if questions
  • Predictive Network and Link Analysis : explore the links between your customers and network of strong social influencers with analytics
  • Predictive Data Management : automated data-set preparation for predictive modeling

Amick Brown can help you realize the predictive powers that you have with your SAP and BI platform provides you.

What is Design Thinking?

Contributed by Kaan Turnali, SAP
“Customer-centric design is about looking out from the inside—rather than outside in”

Today’s organizations face multifaceted problems that are part of increasingly complex business models. Continued expansion of global transactions, supported by partnerships that can span large ecosystems, create unique opportunities and unique challenges for businesses.

These challenges demand multidimensional solutions and require more than just basic applications of current products and services. This is where design thinking comes into play. By applying this framework, organizations can not only address everyday business problems and challenges but also gain a competitive edge.

To stay relevant, companies must innovate without disruption to drive growth and profitability. As Tim Brown, CEO of the design and innovation firm IDEO, puts it in a Forbes.com interview, “Design thinking is all about upgrading within constraints.”


What Is Design Thinking
In its simplest form, design thinking is a process—applicable to all walks of life—of creating new and innovative ideas and solving problems. It is not limited to a specific industry or area of expertise.

It can be as effective in technology or education as it may be in services or manufacturing. It could result in new products and services for customers or improved processes and productivity gains for internal operations. If applied with equal fervor, it can even transform HR, finance, marketing, or operations teams—turning them into lean and agile profit centers.

The award-winning documentary Design & Thinking explores this idea and provides perspectives by well-known subject-matter experts in this space. The Hasso-Plattner-Institute (HPI) at the University of Potsdam School of Design Thinking, in Germany and the Hasso-Plattner-Institute of Design at Stanford University in California are the two leading educational institutions in this field.

Developed by IDEO founder David Kelley, design thinking is defined as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Thus, the method focuses on three main elements of a product or solution: people, technology, and business. All of these aspects evolve around the customer.

The customer drives the current and future state of any business. Products and services, whether they are delivered to internal or external customers, must create intrinsic value and address specific business needs. This cannot be done unless the customer is an integral part of the entire product lifecycle—not an afterthought.

It is accepted that businesses, projects, or teams that lack customer focus are bound to fail. Design thinking makes the customer the main focal point of design for any solution. Plus, it consistently applies the values embraced by this approach, such as empathy, diversity, and ambiguity, as well as recognizing the importance of multidisciplinary teams. Many of these principles reflect ideas that stem from well-known principles and/or best practices. However, design thinking, in essence, incorporates them into a coherent and repeatable process.

Here are my interpretations of some of these principles. You can find others listed here.

  • Success comes from designing integrated solutions in which each part completes the system in whole—not designing fragmented pieces that make up a stack.
  • By getting closer to current or potential users and going beyond distant observation, we have a chance to design by looking out from the inside—rather than outside in.
  • Empathy opens up nerve endings so we can feel what it is like to be in another’s shoes—a prerequisite for customer-centric design. We need to get as frustrated as the users/customers so we can better understand the pain points.
  • By bringing multidisciplinary teams together at the table, we leverage the power of collective expertise.
  • Embracing ambiguity opens the door for human ingenuity—allowing us to chase opportunities for new ideas we would otherwise miss.
  • Promoting the philosophy of “fail early and often” is the key to harnessing the power of rapid prototypes and delivering proof of concepts that resonate and encourage feedback from actual users and customers.

This last one is the closest to my heart because it often reminds me of two famous quotes (available in several variations on the Web). First, there is Edison’s quote about failure and inventing the light bulb: “I have not failed, not once. I’ve discovered ten thousand ways that don’t work.” Then there is Frank Lloyd Wright’s insight “You can use an eraser on the drafting table or a sledgehammer on the construction site.”

To me, design thinking is a framework for ingenuity. It can generate excitement for new ideas, leading to solutions that address unmet needs. Just as business intelligence can be the enabler for faster, better-informed decisions, design thinking can be the driver for better-designed solutions for products and services.

I always argue that passion is the fire that ignites engagement by inspiring what is possible. In the context of business and technology, ideas create the demand for technology that can translate into solutions that drive growth and profitability.

Connect with me on Twitter (@KaanTurnali), LinkedIn and turnali.com

The Overwhelming Power of Analytics in Retailing and B2C: Part 2

Businessman Analyzing Graph




Contributed by  Iver van de Zand, SAP

Retailing and business-to-consumer (B2C) market requirements for online insights are relying heavily on the closed-loop portfolio. The permanent and online interaction of analytics towards rolling planning or predictive models applies all the time. As a follow up to Part One, today I’ll discuss the various ways analytics is applied in retailing and B2C. The situations below are far from exhaustive, but at least they provide insights into what I’ve experienced in various engagements with the retailing sector.

Retailing and B2C segments rely on real-time availability of data insights. Customer behavior, societal influences, the distribution column—they all fluctuate drastically and affect commercial behavior so intensely, that only real-time insights empower the retailer to monitor and adjust the closed loop portfolio. Needless to say, retailing and B2C require in-memory platforms, which provide the calculation and data handling power, plus the scalability, that are needed so badly.

At the base of getting insights are in-memory systems that track every single transaction done in the shops or online. An often-seen solution for this is called SAP Customer Activity Repository (CAR). SAP Customer Activity Repository is a foundation that collects transactional data that was previously spread over multiple independent applications in diverse formats.

Watch the SAP Customer Activity repository video HERE

The repository provides a common foundation and a harmonized, multichannel-transaction data model for all-consuming applications. Retailers can use SAP Customer Activity Repository to gradually transform their system landscapes from traditional database technology to the revolutionary, in-memory database technology.

Assuming the real-time platform and SAP Customer Activity Repository are available, what is the typical scope for this market segment’s insights using analytical components from the closed loop? Let’s have a look.

Basket Analyses

Basket analyses are the core insights that provide information about what people buy at what moment and at what location. We get insights into what is in their “basket.” The mix of products consumers buy is especially interesting. For example, a retailer can use real-time predictive models to predict whether a young female teenager buying red trousers might also be interested in purchasing accompanying earrings.

Sensor techniques can really help the shop employees to focus their advice specifically to the customer’s needs. Consider this shopping scenario:

  • Sensors inform an employee that a customer is picking a blue shirt, sized XXL from the rack.
  • Online analytics and predictive models immediately tell the employee on a mobile device that the customer took the wrong size (based on his buying history) from the rack.
  • The buying history then indicates that the customer typically buys three pieces at once.
  • The employee is also informed that the customer’s profile indicates he might be interested in buying jeans to go with the shirt he’s looking at (based on predictive models).
  • Finally, loyalty card information indicates that if the customer today buys four pieces, an extra bonus will be provided to his savings card.

All this information helps the employee interact with and sell to the customer.

Shop Performance

With shop performance, I mean the ability to use real-time, closed-loop analytics on anShop Performance
overseeing shop level. Sentiment analysis based on, for example, an impacting television show last evening where a popular boy’s band showed their new, hip-colored sneakers, might trigger the retailing group to discount a second article when customers buy similar sneakers. The agility here is crucial—sentiments are notified from social media analyses and action needs to be taken immediately.

Local influences could mean specific sizes of a product are sold very well in one place, but less well in other places. This might trigger shop management to re-allocate stock to other shops. The same thing applies to ranking capabilities—permanently monitoring top-bottom rankings per article, color-item or size is valuable, since the slightest social change (a big event in one specific city) might cause immediate changes in buying behavior locally.

Customer Loyalty

Customer loyalty cards provide the retailer with a wealth of information if used well. The loyalty cards “identify” the person buying. We can see the consumers’ buying behavior, what they buy, and when. Tracking techniques (picking up  mobile devices’ signals when customers enter the store) show us in real time exactly where each customer spends their time in our shop, what is the route that customer typically follows, and what is their average visiting time.Retail

Retailers can go a step further by combining loyalty card information with the customer’s buying history and social media information. This further completes one profile, allowing the retailer to tailor make marketing initiatives on an individual level.

For example, I—as  customer X—might receive a special offer for a new external hard drive from a retailer, since combining data shows that I like audiophile equipment, buy music magazines (basket analyses) and spend quite some time at the electronics department when visiting that shop. The data insight is that I might need (or want) a storage device to store my music.

Customer loyalty cards might also bring great value to the customer retention program. Customers nowadays really quickly change their providers of goods because they are  enormously well informed.

Visitor Analysis


Weather Influences

Weather conditions greatly impact the buying behavior of customers. In general, windy weather has proven to have a highly negative impact on retail sales revenue. Making other general statements is difficult since a specific weather condition can have a positive effect on one type of retail, and a negative on another. Think about how cold weather might improve sales of books but negatively affect sales of handbags, for example. (A nice article focusing on the impact of temperature on shopping can be found at the Summit Blog.)

Likewise, a retail shop’s location—inbound or outbound—and its availability of underground parking are very important in rainy conditions. For retailers, it’s important  to realize that weather conditions have so much impact that they can’t be excluded from operational insights on shop performance. Thus, they must make them part of the closed loop portfolio.

Alternative Business Models

Retail and B2C markets are probably one of the most highly interesting market segments to follow. Why? Well, they’ll be under great change. The “Digital Transformation” age and the availability of information to both the retailer and the consumer are changing everything.

Consumers are not only wanting to know “everything” about their product, they are also shifting to buying (or should I say “renting”) a product experience rather than the product itself. For the latter, think about the accompanying services to a product that the retailer might want to offer. Have a look at this article from Forbes, which describes three trends for retail in the future—instant gratification, borrowing, and customization.

For me, there is enough food for thought to write a Part Three of the series on the overwhelming power of analytics within retailing and B2C. Stay tuned.

Follow me on Twitter – @IvervandeZand.

– See more at: http://blogs.sap.com/analytics/2016/01/06/the-overwhelming-power-of-analytics-in-retailing-and-b2c-part-two/#sthash.YIdYhjL9.dpuf

Artificial Intelligence meets Business Intelligence

By Ashith Bolar, Director of Research, Amick Brown

It’s bound to happen:  Artificial Intelligence (AI) will meet Business Intelligence (BI). In fact, in several places, it has already happened. But let’s take some time to see how this convergence is progressing, if at all.

The first decade of the 21st century was all about Business Intelligence. Towards the end of the decade, big strides were made to harness the explosion of Big Data. The second decade has been mostly about fuelling Business Intelligence with the Big Data. Several companies, large and small, have been making very impressive strides in this direction. However, there is still a lot of room for improvements.

On the other side in the world of computing, Artificial Intelligence has been making slow inroads in all aspects of life. In the last 15 years, AI has been creeping up into our personal lives with applications such as Siri, the entire Google ecosystem, and a myriad of social networking applications. All of this is happening without us realizing the amount of AI happening behind the scenes. Artificial Intelligence has moved out of the academic realm towards the daily lives of consumers.

Much of the business community associates AI with machine learning algorithms. While that’s true, it leaves much of AI underappreciated for its real capacity in Business Planning and Data Analytics. There is more to AI than just recommending your next movie on Netflix and making Google give you better results on your web search.

There are several applications and platforms that transform and summarize a corporation’s big data. However, ultimately it’s the humans that consume this summary of data, to make decisions based on higher human intelligence. I argue that this will change over the next decade. If history is any indication of how accurate our predictions of coming technological revolutions are, I would imagine this transformation will happen much sooner than a decade.

Most of us know Big Data and the Internet of Things that has enabled this explosion. Big Data infrastructure does much of the heavy lifting of cleaning up, harmonizing, and summarizing this data. However, the actual process of deriving intelligence and insights is still within the human realm.

Inevitably, the future of Business Intelligence goes hand in hand with Artificial Intelligence.

The new wave of BI software should be able to perform the basics of building data analytics models without human intervention. These systems should be able to generate hundreds of models overnight. The next step is to build systems that not only generate redundant set of models, but also identify the good models – ones that model reality accurately – and weed out the bad models. The third wave of solutions will be the ones that make a majority of decision making for a company.

In the coming posts, we will explore in more details some of the initial attempts of converging Artificial Intelligence and Business Intelligence.