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Techaisle Blog

Insightful research, flexible data, and deep analysis by a global SMB IT Market Research and Industry Analyst organization dedicated to tracking the Future of SMBs and Channels.

SMB top 10 technology predictions: 2016 and beyond

This is a two part blog article. The first part, published earlier, reviewed the predictions we made for 2015 and the second part, below, focuses on outlook for 2016 and for the longer term (2017 - 2020).

Top 10 Predictions for Year 2016

1. 2016 will see even more intense emphasis on “CIA-Plus”
IT Suppliers will begin to align their offerings with Cloud, IoT, and/or Analytics; products that do not address end-user needs in these areas will be positioned as infrastructure and integration services needed to capitalize on these technologies. This trend, like hybrid IT, will continue into 2017. In 2016, Cloud and Analytics will remain among the top five IT priorities of SMBs and midmarket businesses. IoT will inch its way up into the priority list, though adoption will remain limited.

2. Rise of IoT will be constrained by a lack of real-world examples
From a buy-side perspective, the rise of IoT will need to be fueled by real-world examples showing the benefits of automating tasks and processes within IT and in other sectors. Within the SMB community, we expect sporadic implementation and a lack of concerted effort towards creation of IoT strategy, even though IT suppliers will continue to push forward their solutions hoping to remain top-of-mind in order to claim leadership in this emerging space. Each IT supplier will create its own solution set causing decision and adoption inertia, despite the wave of innovation that we expect to see emerge from the smaller & more agile IoT providers that are able to more easily align IT expertise with real life solutions. Experienced consultants and system integrators in particular will hold sway in matching SMB adopters with suppliers.

3. IoT supplier success will be determined by ecosystem management
On the sell side, the rise of IoT will be accompanied by an intense wave of interest in ecosystem management. It is difficult to buy or sell a “box of IoT”, though providers will claim to provide complete solutions. Parenthetically, this constraint is not limited to IoT. While it is possible to sell a “box of cloud” under the right circumstances, only AWS really manages to do so. And while one can sell a “box of analytics”, the boxes themselves come in a lot of different shapes and sizes. To meet SMB and enterprise buy-side demand for IoT, sellers will assemble coalitions that provide the many products and services that comprise an IoT solution. This will make alliance management a key success factor in the marketplace. The last time alliances determined market leadership; SAP became the global standard in ERP. Niche value added reseller may find a new source of success in IoT.

4. Business transformation will continue to elude analytics users
Analytics users will find that they are not achieving the expected benefits, prompting divergent responses. Some SMBs will find that analytics has not been transformative, and will blame the technology; others will look to move past descriptive and diagnostic views, piloting predictive or prescriptive initiatives. One of these responses is clearly more sensible than the other, but that does not mean it will be universal, at least in 2016. Focus on visualization will increase (mine is better than yours), on how the technology can solve business issues and challenges for SMBs and midmarket customers. Simplified implementation of customer and social analytics will be key drivers of adoption.

5. “Hybrid” will be used more often in conjunction with “IT” than “cloud”
User organizations will accept the notion that their focus on cloud needs to evolve into a focus on hybrid IT, as firms realize that their platforms and management scope must encompass on and off-premise systems. Truthfully, there is still a lot of work to do in cloud adoption. But the nature of the discussion has changed from “what and how do we move to the cloud?” to “what do we do to build an integrated, manageable infrastructure?” In 2016, there will likely no longer be an infrastructure debate about use of cloud, but there will be an important emerging discussion around managing hybrid IT.

6. Collaboration will drive “silo” to the realm of four-letter words
Anywhere, anytime also means any type of collaboration. SMB & midmarket businesses will look for unified shared workspaces that allow employees to enter into the workspace from any entry point to work together, collaborate and interact. Collaboration solutions cannot be deployed on stand-alone platforms – they need to be viewed as a framework for integrating multiple capabilities, native to multiple applications.

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2015 Predictions Review: did IT live up to the hype in 2015

December has traditionally served as the occasion for the publication of New Year forecasts. It’s understandable that we want to look ahead to the sources of opportunity that lie ahead. But in the business world, December also marks the beginning of the review season. And while detailed forecasts focus on the next twelve months, the planning horizon needs to look a little further, so that tactics provide support for business strategies, rather than simply delivering a series of course adjustments.

This is a two part blog article. The first part, below, reviews the predictions we made for 2015. Second part will focus on outlook for 2016 and for the longer term.

A look back – what was it we said was right around the corner, again?

Here are the issues we highlighted, “Ten predictions for 2015 – and five issues to keep an eye on for 2016 and beyond” and how we think we did in our prognostication.

The Top 10 for 2015

1. Hybrid arrives – not as a strategy but as the result of many discrete decisions

With the benefit of today’s perspective, we might fairly say that in 2015 and for several more years to come, a more apt description of hybrid is journey rather than destination. Digging into the detail, though, we believe our prediction that “an ability to manage hybrid infrastructure will become a key corporate IT requirement in 2015” has been borne out by the focus on tools and strategies (ranging from Docker to Agile) that we saw throughout the year. In Techaisle’ SMB Cloud adoption studies, there was a sense of growing ubiquity in the usage and plans for private, hybrid and public cloud. Use of hybrid cloud continued to increase as both a conscious strategy and as a reaction to use of both public and private resources within a single infrastructure; by the end of 2015, two-thirds of companies with 100-999 employees were using hybrid models.

2. Collaboration becomes a much bigger concept

In 2015, collaboration began to expand beyond file-sharing to become a necessary tool for driving decision-based agility, fostering innovation and extending customer intimacy. Collaboration is a process rather than a discrete outcome. Our key notion that collaboration “extends beyond the corporate staff (and as a result, beyond large enterprises) to include customers” clearly did reflect strategies and investments in 2015. Within the SMB segment collaboration is increasingly becoming a central component to virtually all business activities rather than a means to enable connections between discrete tasks. Other changes in this area will further reshape collaboration, but you’ll need to refer to the “forecast” part of the blog for that discussion.

3. Collabmobilicloud becomes a management reality

The core concept explained that despite vendor tendency towards defining collaboration, mobility and cloud as separate domains, both enterprise and SMB users have started viewing them as integrated components of business solutions. The user belief that collaboration, mobility and cloud should all be attributes of modern applications has become clearer, and even suppliers are starting to recognize the importance of an integrated collabmobilcloud approach.

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Big Data in the Cloud - an ideal solution for SMB banks

Wall Street Journal carried an article on how regulatory burdens had made community banks “too small to succeed” despite performing better than larger banks regardless of being better capitalized and having lower default rates.

The advent of cloud technologies has the potential to change WSJ’s dire prognosis.

Cloud may have first been introduced as a means of reducing CAPEX and/or overall IT costs, but today, it is viewed by small and midmarket businesses as a means of increasing business agility and of introducing capabilities that would have been cost or time-prohibitive to deploy on traditional technology. Complementary to cloud, big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether for increasing sales, improving products or detecting fraud. SMB banks are a specific segment of SMBs who can derive the benefits of customer insight while meeting their mandatory regulatory requirements.

Techaisle classifies SMB banks as those below $10B in assets and medium sized banks as those between $10-100B in assets. SMB banks below $10B in assets often called “community banks” play a very important role in the ecosystem of SMB businesses. Although FDIC, OCC and FRB have different definitions of community banks, it is important to note that these smaller banks not only accounted for nearly half of the total of about $600B outstanding small business loans at the end of 2014 but also play a disproportionately major role in the $1.8 trillion residential mortgage origination market.

Unlike large banks, SMB banks are characterized by George Bailey in “It’s a Wonderful Life”. These banks usually have keen insights on their customers based on personal relationships and carry a tremendous amount of tribal knowledge about their customers which they use to make business decisions. While this corpus of knowledge may not be codified it does make a difference in their business operations. But is that enough in today’s hyper-competitive economy where the relationship is being increasingly controlled and dictated by customers?

Then there is another question, are these smaller banks doing enough to detect fraud? High-risk businesses that have been denied services by large banks tend to move their business to smaller banks who are less equipped to analyze these risks. These smaller banks are unknowingly exposing themselves to fraud as well as compliance risk. Regulations are agnostic to bank size and equally unforgiving of SMB banks as they are of large banks. A cloud-based analytics solution may just be the recipe for success for the smaller banks. In fact, these banks are no different than midmarket businesses (or even small businesses) in their objectives of adopting big data.

techaisle-top-business-drivers-for-smb-big-data-adoption

Monitoring, analyzing and reporting very large volumes of data are typically the largest components of regulatory costs for SMB banks. Many often use antiquated technology and manual processes to manage their compliance requirements. Banks that are able to automate the process of managing data for regulatory requirements can have the added benefit of getting a unique view of their customers through one single technology solution.

According to Shirish Netke CEO, Amberoon, a provider of Big Data solutions for banks, “A lot of the data that is required for regulatory compliance can also be easily parlayed into getting insights on the banks customers and improving business”. Amberoon has built a banking solution for SMB banks provisioned on the IBM SoftLayer cloud.

Security & privacy (especially FFIEC requirements), traditional inhibitors of cloud adoption, are a legitimate concern for banks. After all, banks are the custodians of individual’s money, facilitators of trade and commerce and life-line of businesses. However, it may be argued that these inhibitors have already been successfully addressed by service bureaus. A very large percent of SMB banks outsource their core banking system to service providers such as Fiserv and FIS Global who have built very large scalable service bureaus with the economies of scale afforded by centralizing technology resources.

Aptly put by Noor Menai, CEO of CTBC Bank. “Outsourced technology services are nothing new in the banking industry. There is a compelling reason to use big data technologies in banks if they are available at an affordable cost in a secure manner. Cloud has the potential to provide both”.

Big data analytics in the cloud can be an execution advantage, and may even propel the SMB banks to leap ahead of larger banks on solutions that address both regulatory necessities as well as gain competitive edge from customer analytics. Historically, Siebel, an on-premise solution, was usually deployed in large enterprises and was out of reach for smaller businesses. Salesforce, a cloud solution, changed the perception, adoption, usage, affordability and provided immediate business outcomes. Today Salesforce is used by both SMBs as well as large enterprises.

Combining the benefits of cloud with the advantages of big data analytics may just be the prescription that SMB banks need for business growth (cross-selling, upselling services), meeting regulatory requirements such as KYC/AML/BSA and deep-diving into fraud detection.

One should also not forget that big data implementations require a unique combination of technical, operational and business skills to be used in a sustained manner. Needless to say, these skills are in short-supply but affordable by deep-pocketed larger banks. While some smaller banks including community banks can spend the money to experiment with big data pilots, they do not have the capacity to go through expensive iterations to get it right. While larger banks have the luxury of choosing between on-premise big data versus cloud big data, for smaller banks the choice could very well be between either doing big data on the cloud or perhaps not doing it at all. The remaining question therefore is – which big data cloud supplier will take the lead in educating, evangelizing and then executing on the needs of SMB banks.

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SMB big data adoption - from over-hype to must-have

Techaisle’s quantitative study (survey of nearly 900 SMBs) on SMB & Midmarket Big Data Adoption and Trends shows that 7 percent of small businesses and 20 percent of midmarket businesses are currently using Big Data solutions and that another 17 percent & 38 percent respectively are planning to adopt within the 1-2 years. These businesses are looking at a big data solution from 3 perspectives:

First, what are the organizational needs, second, what could be served as a solution and, third, what could be the best combination of the tools and technologies available today which will provide value add. Based on all one should decide on a solution because the Big Data space is very enormous and could be applied for any domain,” aptly quoted by CIO of a midmarket firm who has successfully implemented big data solutions in his organization.

Common findings that run through corresponding depth interviews (over 60 interviews conducted globally) conducted by Techaisle, Insights from the Trenches of SMB Big Data Implementers, are:

  • PoC – more is better, timing is of essence
  • Cost efficiencies of Hadoop, especially Cloudera
  • Plethora of tools deployment – emergence of Spark and Flume
  • On-premise only – now and the future
  • Must conduct skills training and gap analysis
  • Lessons learned – not to underestimate complexity but uniform voice – go for it

The promise of superior data-driven decision making is motivating 24 percent of US small businesses (1-99 employees) and 58 percent of midmarket businesses (100-999 employees) to invest in Big Data technology.

us-smb-current-planned-big-data-adoption

In addition, the possibility of analyzing a variety of data producing action-driven business insights is too big to ignore for midmarket businesses. This represents a sizable opportunity considering that the segment is relatively new, it requires a certain level of IT sophistication and a history in linear investment in information technology enablers to be successful.

smb-current-planned-bigdata-by-techaisle-it-sophistication-segments

Specifically, midmarket attitude towards big data has transitioned from “over-hype” to “must-have” technology with the increase in employee size. Only 11 percent of midmarket businesses consider big data to be an over hype suggesting that it has crossed the tipping point faster than similar sentiments for cloud adoption at its introduction. However, nearly one-fourth of lower mid-market businesses still consider it to be over-hyped yet 29 percent think that it will be an important part of their business decision making process.

Nevertheless, SMBs face many challenges in implementing big data solutions.

top-5-challenges-being-faced-by-smbs-in-implementing-bigdata-solutions

There are many different tactical objectives for deploying big data projects and SMBs are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations, and improved customer service.

CRM solutions had first established the analytics for analyzing customer data but 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 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 for generating sales, improving products or detecting fraud. It is therefore not surprising that globally SMBs and midmarket 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.

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