GIANT 2016: SaaS solution opens up SME market
Three years after the launch of the original GIANT product, Fusionex has launched version two of its platform, GIANT 2016. Improvements include simpler and faster navigation, with natural language features added to the interface making the product easier to use. Support for R, a specialist programming language for data analytics, and Python, a general programming language that is increasing in popularity, have been improved. Fusionex has also added smart maps features, the ability to make parallel queries, along with streaming insights and more charting functions.
With GIANT 2016, management hopes to open up the big data analytics market to companies of all sizes by enabling functionality to be tailored appropriately (eg some of the high-end features like real-time processing are not required by all companies).
Launched in June 2016, GIANT 2016 has already announced three significant contract wins with an integrated holiday resort in Asia to use GIANT 2016 to optimise marketing strategy, a Japan-based international travel, leisure and hospitality group, to use GIANT 2016 to support its operations in the Philippines and, most recently, with Bursa Malaysia Berhad, Kuala Lumpur's Stock Exchange, where GIANT will enable it to keep track of the multitude of stock and price movements in the market.
GIANT differentiates on price, ease of use and completeness
Big data solutions are built on a growing number of crucial and evolving software elements (Exhibit 3). Typically, the cost to the user of setting up systems and understanding the various software elements is considerable. Big data projects with the major vendors, such as IBM, SAP, SAS and Oracle, generally command multi-million dollar price tags and yet the customer can still be left with a solution that is difficult to use and adapt. GIANT has been designed to be self-serve and intuitive to use by anyone in an organisation – not just those with database management or coding experience. It was recently made even easier by the integration of natural language processing (much like Google Search).
Based on average customer numbers, we estimate that Fusionex charges average annual subscriptions of approximately $300,000 per implementation compared to millions of dollars charged by the US and European industry majors to set up and license a big data solution. The SaaS version targeted at SMEs will have a considerably lower entry level price point. A key part of Fusionex’s ability to create and deliver products that are very cost competitive against the US and Europe-based major software vendors has been its lower cost of product development and, most importantly within this, the lower cost of local labour. Management states that it does not experience any significant problems in recruiting staff of the right calibre either in Malaysia or internationally, but some training is often required for some of the more specific applications and areas, particularly in the big data environment. There is also likely to be a cost advantage flowing from the fact that Fusionex’s product includes a number of layers in the big data supply chain.
There are many competitors for all of the elements of the GIANT product. However, products from the market leaders such as oracle, SAP and IBM combine a number of solutions. We are not aware of any similar solution that covers such a range of big data system elements in one package. In the area of data management tools companies like IBM, DataStax, Informatica and Syncsort have strong positions. In the visualisation and analytics area Tableau, Karmasphere, Datameer, Tresata and SAS Institute are among the leading names. These players in general have narrowly defined products and reach their markets only via larger resellers or software companies. These resellers will in turn place the product alongside other technologies, from their own library, from other vendors or from open source.
Exhibit 3: Big data supply chain
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Customers – blue chip names across many sectors
Fusionex’s customer list is a mix of quality names across a wide range of segments ranging across finance, electronics manufacturing, hospitality and media. Customers are both local and international names and include DHL, Las Vegas Sands, Starwood Hotels & Resorts, Lotus, Intel, Yeo’s, Aeon, Dell, TNS Group (Taylor Nelson Sofres), Brother Industries, Canon, Siam Cement, Air Asia, Hewlett-Packard, CIMB Bank, Takaful Insurance, MetLife, Resorts World Singapore, Volvo, Carrefour. GroupM, Jones Lang LaSalle, UEM Sunrise and Mitsui, among others.
Many of Fusionex’s implementations have been for local subsidiaries of global businesses that would typically be expected to choose solutions from the majors. Having proved itself capable at the local level, Fusionex is increasingly providing similar services to other local operations of these customers across South-East Asia and globally.
It has also received a number of accolades from industry bodies including Most Outstanding ICT Company in Asia by the Asian-Oceanic Computing Industry Organisation (ASOCIO) in 2015 and the Innovation Award at the 2015 Microsoft Worldwide Partner Conference. The inclusion of Fusionex as another “relevant vendor” for the first time in Gartner’s February publication of Magic Quadrant for Business Intelligence and Analytics Platforms is an encouraging signal that the company is making its presence felt on a global basis, despite its relatively small size.
Applications and efficiencies – case studies
Fusionex asserts that for a typical customer, it will derive approximately 10-30% savings on down time, 10-35% operation expenditure efficiencies, or drive double-digit increases in sales growth via customer profiling and product analysis. A good way to illustrate the power and potential of GIANT is by describing some of its applications.
Semiconductor manufacturing
The work undertaken with Intel is probably the highest profile and best documented of GIANT’s applications, with the implementation being the subject of a white paper. Intel worked with Fusionex, Cloudera, Dell, Mitsubishi Electric and Revolution Analytics (now part of Microsoft) on an IoT big data analytics project.
Semiconductor manufacturing is probably the most technically demanding manufacturing environment. Semiconductors, and particularly those that Intel makes, are high-value, ultra-high precision items that are manufactured in bulk on extremely expensive capital equipment in a highly complex process. Downtime can cost millions of dollars per hour, reworks and repairs of defective products are impossible and manufacturing equipment failure can be not only expensive but also dangerous. There is a vast amount of data generated within a semiconductor manufacturing facility. Historically, however, much of this data has been applied in a single use, for example to find out if a temperature is too high or too low, but big data technologies provide the ability to better consider these variables over time and to understand how they relate to each other.
Together with its partners, Intel gathered the data from its plethora of sensors over a period of time and looked at it alongside metrics such as equipment fail rates and product testing accuracy. A number of uses were found and applied over the life of the project, including predicting the failure of key components in manufacturing equipment, identifying where chips have not been successfully attached to substrates and using image analytics to identify and predict faulty products.
Intel’s use of Fusionex technology demonstrates that, despite its substantially lower price tag, GIANT can deliver an application where one might normally expect to find a US or European industry major’s product and, just as important, that global corporations with bleeding-edge technology skills recognise this.
Although the applications made by Intel are industry specific, it is clear that the streaming analysis of volumes of data and allowing users to simply manage and apply data is applicable across many manufacturing, process or extractive industries from semiconductors to food to oil. In fact, it is difficult to identify a large-scale manufacturing process for which it would not be relevant.
Hotels, resorts and theme parks
Fusionex has a GIANT customer that is a leading player in the Asian hotels and resorts market offering travel, hospitality, theme parks and conference facilities in a number of countries. Handling hundreds of thousands of visitors every year, both corporate and private, the company has a vast amount of information about its customers’ behaviour.
There are clear peaks and troughs in demand, across each day, week and year, and a high fixed-cost base. This means that there are significant potential benefits from managing occupancy and utilisation in hotels, theme parks and resorts. With GIANT from Fusionex, the client was able to bring together the masses of data to which it has access, from bookings, customer preferences, social media and even weather data, to analyse it and extract useful information and insight. As a result, the client is better able to predict and manage demand, yielding occupancy rate improvements of over 20%, with resulting operational efficiency gains of over 60%.
As for Intel, this is just the start for this client and, more importantly, for this application. We believe that this client intends to roll out the GIANT solution to a number of its sites across Asia as a result of the success it has seen with its initial implementations. Although we believe the scale of this client’s sites is large (including some of the biggest and best known in Asia), the relatively low cost of GIANT suggests that it is a relevant solution for worldwide hotels, resorts, conference facilities and theme parks.
Widening its addressable market
The market opportunity is significant. Management is widening its sales capabilities by increasing its international presence directly, as well as by establishing an increasing number of indirect sales channel partners.
Greater emphasis being placed on indirect channels
Fusionex makes most of its sales directly and works in tandem with Dell, Hewlett-Packard, Accenture, Microsoft, IBM and EMC for projects where these leading vendors see opportunities to increase their sales by working alongside or promoting Fusionex. These sorts of relationships now extend deep into the big data ecosystem. Fusionex also has partnerships and certifications with both Cloudera and Hortonworks, the leaders in providing big data platforms based on Hadoop, and Revolution Analytics, the leader in software and services relating to the R data analytics language. Fusionex’s c 15 sales representatives work directly with these partners and these sales are regarded as direct sales.
Since 2015 Fusionex has also been focusing on increasing its use of indirect sales channels as a way to cost-effectively scale its reach. The proportion of sales coming from indirect channels is currently 30-35%, and in the past management has indicated that it hopes to see this increase to 70%. The impact of this on gross margins could well be negative, if margin is sacrificed to partners, but the increased revenues should more than offset the added cost. In mid-2014, it was announced that the global technology distribution giant Avnet had joined Fusionex in a partnership arrangement and it has since announced partnerships with Mesiniaga Berhad (one of the biggest ICT solutions provider and systems integrators in Asia) and VADS (one of Malaysia’s leading integrated managed ICT service providers).
Establishing channel relationships is a key step in growing the overall customer base. However, motivating these channel partners to actively market a vendor’s products can be harder. Fusionex has decided to support its product visibility by launching a significant digital marketing campaign, and enhanced use of conferences and exhibitions to drive awareness and sales.
Internationalising the business
In FY15, 24% of sales were from beyond the ASEAN market, compared to 21% in FY14. While Asian markets are considered to be at a fairly early stage of development when it comes to the deployment of big data solutions, it is evident that interest for big data solutions in ASEAN nations is growing, as evidenced by the first Strata Hadoop World, the leading global big data industry event, in Singapore in December 2015. Since the IPO in 2012, the company has established offices in Indonesia, Hong Kong/Macau, Thailand and Singapore. We believe that the recent fund-raising will be applied in part to taking the international expansion a step further, with the establishment of a significant sales and development presence in the Philippines and plans to expand into Australia, Greater China and Vietnam.