CRM has become a core application for businesses and we have already seen that Sales Force Automation and Marketing Automation functions have been quickly incorporated along with Business Intelligence. All of these can use the same or linked tables to provide a 360 degree view of the sales and marketing process. However, today, we have finally come to a place where it should be easy enough for SMBs to plan and execute business strategy using a structured performance management system, like the Balanced Scorecard. Key Performance Indicators (KPIs) should be a standard part of the application architecture as should a meta-directory of KPIs that all applications can access. To measure the effectiveness of Sales, Marketing, Operations, and industry-specific activities, each area should have standard metrics and access to benchmark data that lets the SMB know how they are doing compared to peers, but rather than only using historical data it should be based on forward-looking objectives (leading indicators) that are tied directly or indirectly to activities designed to ultimately improve financial results. SMBs are seriously interested in measuring elusive objectives like Return on Marketing Investment, Optimal Pricing, Cost of Acquisition, Lifetime Customer Value. They want integrated applications that can not only measure these objectives but also be able to optimize effectively. This is what we call the Enterprise Performance Management (EPM).
For EPM applications to be really effective, they should be able to collect data from all applications and break into several areas; for people, productivity should be monitored through activity and results (as it already is in the new generation of SaaS applications), and effectiveness of software and equipment should be measured through algorithms that follow click paths, analyze application usage, optimize the process flow and usability of the systems. In some cases, like network optimization, filtering potential employees and ecommerce, systems should optimize themselves and human intervention should only be required when something is way outside the parameters defined by the administrator – who may increasingly be the LOB management.
With the EPM (Enterprise Performance Management) system SMBs will have a new attitude and culture that values and uses data visualization as the quickest way to gauge overall performance and specific areas of interest at a glance.
Most SMBs that have used CRM and ERP systems within the past few years are familiar with the dashboards that are available with many of these applications, either embedded or purchased separately. We believe that Dashboards will continue to evolve and be dynamic in several ways; the way they use data from subsystems like ecommerce and other real time feed sources, the way users can personalize the layout of their dashboards. Similarly, within the EPM, the actual KPIs should be dynamic and have the ability to build KPIs “on-the-fly” by calculating variables on the screen and saving the result in a meta-repository for all to use. It will have to become the norm.
While several SaaS vendors allow this kind of metric building and start the user at a dashboard, we have yet to see anything targeted to the mid-market or SMBs that connects the performance across front office, production, fulfillment and customer service. NetSuite does it to some extent almost out of the box. The market has to catch up. While this level of functionality is an excellent target, small businesses can probably get by with a good understanding of leads, opportunities, customers, invoicing, billing and customer service (or the appropriate subset) by integrating together several applications from different IT vendors. But the need for EPM is genuine and the industry has to quickly design solutions to empower SMBs with enterprise-level EPM technology at an affordable price.
Techaisle Blog
Once a decision was made to embark on a big data deployment project, the mid-market organization tended to quickly align behind the initiative. They did realize that big data was not a typical cloud application deployment where independent department purchases could be made, nor was it infrastructure deployment where only IT could be involved. Big data required a new type of alignment between business heads, namely, Marketing, Finance, IT and a completely new set of players known as data scientists or data analysts.
Study shows that businesses are moving from “whack-a-mole” analytics to “business perspectives” to get newer insights into their operations and better knowledge about their customers as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers. There are many different tactical objectives for deploying big data projects but the top among them are sentiment monitoring, generating new revenue streams & improving predictive analytics. And businesses are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations, improved Customer service.
In a parody of Start Trek, Silicon Valley technology companies describe their business goal as “Scale, the final frontier…”. Mid-market companies, defined as those having 100-2500 employees, may indeed provide an opportunity to emerging technology vendors to scale their business. According to Techaisle, a market research firm, these 800,000 global companies spend $300B on IT and are sought after by technology vendors big and small. In the last decade, technologies such as Cloud, SAAS and Virtualization have reached scale with a large number of mid-market companies as early adopters. Intuit, Salesforce.com, NetSuite and Amazon are just a few examples of companies who have relied upon mid-market companies as a key building block for their business.
What does this mean for Big Data? To find out, Carpe Datum Rx spoke to “SMB Guru”, Anurag Agrawal, CEO of Techaisle and the former Head of Worldwide Research Operations at the Gartner Group. Techaisle recently talked to 3,300 global businesses about their Big Data adoption plans. Here is an excerpt from our discussion.
The SMB Market is considered the Holy Grail for technology vendors because it is hard to penetrate. Does your research show that mid-market companies will adopt Big Data before large enterprises do? Are they the early adopters of this technology?
Yes, you are right the SMB Market is the Holy Grail as it is hard to penetrate but with the highest potential. To elaborate, there are slightly over 70 million small businesses and 800,000 mid-market businesses worldwide. They constitute over 97 percent of the business segment. And their collective IT spend is projected to grow by 6.5% between 2013 and 2016 which is quite a lot faster than the Enterprise segment. To really identify the SMB segments and their type of technology spend is a mind-numbing exercise due to the sheer volume of data points. This is compared to the enterprise segment where there are fewer companies and larger dollar amounts being spent.
To answer your second question about whether mid-market businesses will adopt big data before large enterprises, let us look at some facts. Cloud computing started as an enterprise play, however, it was quickly discovered that SMBs would be the more relevant target segment with a faster path to adoption. Similarly, as enterprises adopted Virtualization, vendors shifted their focus to the SMBs with some very creative solutions. Mid-market companies, defined as those with 100 to 2500 employees could certainly be the early adopters of Big Data. We recently did a study where we surveyed 3,360 mid-market businesses worldwide covering all regions – North America, Europe, Asia/Pacific and Latin America. What we found is that the promise of superior data-driven decision making is motivating 43 percent of global mid-market businesses to at least look at Big Data technology. And above all, 18 percent of mid-market businesses are now investing in big data related projects.
In the mid-market segment, there is also a competitive imperative to understand customers, create innovate products and improve operational efficiencies. They are not burdened with too many silos and large legacy systems deployments. The absence of large legacy systems is an important point to consider because it makes mid-market businesses more agile to implement new types of solutions that solve their business problems. It is expected that in year 2016, global SMBs would spend US$3.6 Billion on big data solutions exhibiting a growth rate that is faster than what was exhibited by cloud computing solutions.
We understand that you cast a very wide net to get your 43% number. Is there a consistency in the sentiment on big data across different parts of the world?
Yes, we had to cast a wide net to really understand the adoption and trends within mid-market businesses. And yes, there is a difference across geographies and employee sizes. North America has both the largest market and the highest level of adoption in Big Data overall. In terms of actual deployment activity, the market grows in relation to the size of the companies. Additionally, mid-market business attitude towards Big Data transitions from “Over-Hype” to must-have technology with the increase in employee size. Let me give you some examples. A small-to-mid-sized bank is developing a Proof of Concept for fraud analytics. Another example is of a small advertising agency that is trying to deploy digital advertising analytics. So big data is not only within the radar of enterprises, the same problems exist across all sizes of business, only the volume of data, available budget and the required simplicity varies. The problem is that we all get caught up in technology which instills a sense of fear. We have to shift the conversation from technology to solving business problems.
Big Data adoption is often stalled by a lack of knowledge or understanding of the technology and its capabilities. Do mid-market companies have a better understanding of this technology than large enterprises? Do they have an advantage over large enterprises in implementing effective solutions?
You are right. Three things – Technology, Resources and Data are the biggest roadblocks for big data project implementations within mid-market businesses. In recent years technology and technology options have evolved extremely rapidly for an average business to understand, evaluate, purchase and implement. Big data is no different. Mid-market businesses consider big data as very complex resulting in very steep learning curves. The complexity gets further exacerbated with lack of experience, lack of skilled manpower and innate difficulty in identifying external consultants who would be the right fit for their big data business objectives and budget availability. In spite of challenges, the study shows that there have been some successes when business units, IT & data analysts exhibit extraordinary alignment.
Our study shows that mid-market businesses typically start their big data journey in one of four ways and the highest success rates have been achieved when IT and data analysts work with external consultants from project inception. It is still very early days for these businesses to fully embrace big data but the seeds are being planted. And we believe that these businesses may very well race ahead of enterprises with their deployments as technology becomes simpler and consultants become experienced. As we like to say it, SMBs could be the path to big data simplicity.
You talk about the linking of structured and unstructured data. Why is this problem so important compared to all the others?
The issue of analyzing data from diverse sources leads a mid-market business to naturally consider linking structured and unstructured data. If we look back, CRM solutions had first established the need for analyzing customer data. However, the data was mostly two-way transactional structured data. This changed when customers began visiting business websites to explore, browse and perhaps make purchases thus leaving behind a trail of information. And everything changed with the onset of social media, blogs, forums, wikis and opinion platforms where the identification of false positives and negatives became difficult and knowledge about the customer and resulting segmentation became an inaccurate undertaking. Big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights for generating sales, improving products or detecting fraud. Thus the importance of linking structured and unstructured data to analyze social media data, web data, customer and sales data along with click-stream machine generated data and even communications data in the form of emails, chat, and voice mails. But extremely limited expertise creates a major challenge. If they can figure it out, one-fourth of mid-market businesses say that they will use big data as an integral part of their overall analytics efforts. The possibility of analyzing a variety of data producing action-driven business insights is too big to ignore for mid-market businesses.
How are big data projects getting started globally? Are they championed by LOB managers? Are they getting adequate support from executive management? Are customers demanding it?
The study reveals that the initiators are marketing, finance or operations and the ultimate user of the analytics is the business user. Big data requires a new type of alignment between business heads, namely, marketing and finance (main drivers of big data projects), IT and a completely new set of players known as data scientists or data analysts. As I mentioned before, once the decision is made mid-market businesses show an extraordinary alignment across departments. Our study shows that mid-market businesses typically started their big data journey in one of four ways. However, the highest success rate was achieved when an external consultant or organization was brought in to develop proof of concept, advise on database architecture and ultimately develop the big data analytics solution right from the moment of project inception.
What is one piece of advice or Carpe Datum prescription can you share for our members?
You have adopted cloud, you have adopted mobility, you have adopted social media so do not be afraid to develop Big Data analytics proof of concepts. Do not ignore big data just because of perceived complexity and big data solution providers’ inability to create bite-sized messaging that directly address pain-points. Do not forget that business intelligence has now become one of the fastest solutions to be adopted by SMBs and mid-market businesses. If done right, big data will address three key pain points: Increased sales, More Efficient operations, Improved Customer service.
Cloud computing started as an enterprise play, however, it was quickly discovered that SMBs will be the more relevant target segment with a faster path to adoption. Similarly, as Virtualization market started getting fully penetrated within the enterprises, vendors shifted their focus to the SMBs with some very creative solutions. As far as big data is concerned SMBs are starting to show interest and even adoption. However, there is a stark difference in approaches between mid-market businesses and small businesses. While mid-market businesses are experimenting with bespoke solutions, small businesses are gravitating towards a multi-tenant, aggregated and federated big data solution that has a mix of publicly available data and their own internal data.
It is expected that in year 2016, global SMBs would spend US$1.6 Billion on big data solutions exhibiting a growth rate that is faster than what was exhibited by cloud computing solutions. Cumulatively between now and end of 2016, SMBs itself would have shelled out US$3.9 billion on big data solutions. This spending includes hardware, software and services.
So why are many big data solution providers ignoring SMBs? Simply put, because of perceived complexity and inability to create bite-sized messaging that directly address SMBs pain-points. But they should not forget that business intelligence has now become one of the fastest solutions to be adopted by SMBs. If done right, Big data address three key pain points of SMBs: Increase sales, Efficient operations, Improve Customer service.
Promise of Superior Decision Making
Let us take Techaisle’s recent global mid-market businesses’ Big Data Adoption & Trends study which clearly shows that the promise of superior data-driven decision making is motivating 43 percent of global mid-market businesses to either invest in or investigate Big Data technology. Out of these, 18 percent of mid-market businesses are actively investing in big data related projects. The possibilities of analyzing a variety of data sources, producing action-driven business insights is too big to ignore for these businesses.
Similar to cloud, the attitude towards Big Data is transitioning from “Over-Hype” to “Must-Have” technology with the size of business. Even within the businesses that consider big data to be over-hyped, 29 percent think that it will be an important part of their business decision making process in the future.
Extracting Business Perspectives
Business intelligence by itself has provided enough business insights, however, mid-market businesses are now looking for extracting business perspectives to drive superior decisions and ultimately achieve superior results. Extracting business perspectives has become important as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers and partners.
CRM solutions had first established the analytics for analyzing customer data. However, the data was mostly two-way transactional data. This changed when customers began visiting business websites to explore, browse and perhaps make purchases thus leaving behind a trail of information. IT vendors and mid-market businesses figured out the need to analyze the data and combine it with transactional information.
However, everything changed with the onset of social media, blogs, forums, wikis and opinion platforms where the identification of false positives and negatives became difficult and knowledge about the customer and resulting segmentation became an inaccurate undertaking.
Big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether be for generating sales, improving products or detecting fraud.
It is therefore not surprising that global mid-market businesses are turning towards big data analytics to analyze social media data, web data, customer and sales data along with click-stream machine generated data and even communications data in the form of emails, chat, voicemails.
Leap of Faith or Solution Readiness
Analyzing data from diverse sources leads a mid-market business to naturally consider linking structured and unstructured data. This also drives them to evaluate and select the technology that can be used for simplified implementation. Simplified implementation is important because mid-market businesses do not yet have in-house capabilities to analyze unstructured data and those that have them consider the capabilities at best rudimentary.
Big data therefore is a major leap of faith for mid-market businesses resulting in treating big data analytics projects usually as separate to the existing analytics within the business. More aggressive adopters are planning to use big data analytics along with other analytics in a coordinated manner so that one does not become an inhibitor for the other.
In recent years technology and technology options have evolved extremely rapidly for an average business to understand, evaluate, purchase and implement. The complexity gets further exacerbated with lack of experience, lack of skilled manpower and innate difficulty in identifying external consultants that would be the most right fit for their business objectives and budget availability.
In spite of challenges, the study shows that there have been some successes when business units, IT & data analysts exhibit extraordinary alignment. Our study shows that mid-market businesses typically started their big data journey in one of four ways. Highest success rates for project implementation and generating new insights have been achieved when IT and data analysts work with external consultants from project inceptions.
SMBs as the Path to Big Data Simplicity
The global SMB spend on big-data related deployments will cross US$1.0 billion in 2013 which is a 32 percent increase from 2012. SMBs are still experimenting to see if big data analytics can provide newer insights into their operations and better knowledge about their customers. It is still very early days for small and mid-market businesses to fully embrace big data but they are planting the seeds in terms of re-architecting their IT infrastructure to plan for the future. But we believe that SMBs may very well race ahead of enterprises with their deployments as technology becomes simpler and consultants become experienced.
