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Adapting To Digital Transformation

From incorporating a faster and more efficient fleet-tracking technology to application delivery, digital transformation has become a permeating voice in talking about taking businesses to the next level by fast-tracking their time to market, reducing optimization costs, and creating a fluid business model.
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Businesses are getting ready for this year’s Black Friday and Christmas shopping season. Leading retailers attempt to predict the hottest trends, define reasonable prices and foresee a time-slot an average consumer will spend on a particular product. With big data analytics and powerful machine learning tools, their predictions will be the most accurate.

The term “big data” has become a buzzword for sales teams across nearly every industry over the past few years. Companies have collected vast amounts of data from leads and transactions which no single person would ever be able to process. According to an MIT Sloan Management Review survey of companies earning 500M+ in sales, at least 40% of companies are using machine learning tools to increase performance. From providing insights on leads to recommending current customers new products, machine learning can revolutionize the sales industry in several ways.

1. Added Customer Support

According to Salesforce’s Adam Lawson, customer experience is the most important variable separating successful and unsuccessful sales teams. ML will allow for significant improvements to customer experience — with the ability to proactively follow up with leads, customize the user’s experience and answer questions via chat (called chatbots), every customer will have an experience tailored to their preferences and needs.

2. Improved Forecasting

Within the last few year, advanced lead scoring has become an extremely popular tool for sales teams. Lead scoring, which uses ML, looks at collected data on prospects, such as their budget, size, past sales, and interaction with marketing emails then formulates a score which will project interest and the likelihood of a sale. This process reduces the number of dead leads and focuses a sales team on converting strong leads to clients.

3. Personalized Suggestions

In the retail industry, you may have noticed the text “other customers purchased” or “you may also be interested in,” followed by a list of similar or complementary products. These suggestions are thanks to ML, which allows supporting a consumer-centric approach, through the analysis of sales patterns, purchase histories, and data consumption. Companies like Amazon, Spotify, and Netflix are already employing this solution to suggest additional content for customers. As this technology becomes more readily available, smaller retailers and SaaS companies will begin to follow suit.

In the sales industry, ML can streamline the entire consumer relationship from the first point of contact to customer support. As machine learning continues to improve both sales teams’ and customers’ experiences, its influence over the sales industry will only increase over the next few years.

Want to keep your sales high even after the holiday buying boom is over? Contact us at ELEKS. We’ll make sure your team is equipped with the machine learning tools your company needs to get ahead.

Originally published at eleks.com on November 9, 2017.

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It's 2017 and IoT continues to be a buzz. Appearing more frequently in almost every news articles regarding technology trends, digital transformation and the next "industrial revolution". However, behind the seemingly robust industry boom, rates of IoT adoption across Southeast Asia seems to be at a more conservative level.

Enterprises and organisations are cautious of adopting IoT for various reasons, and it is important for solution providers to understand these gaps in order to address enterprises' challenges and bring IoT to a wider reach.

1. Security

Arguably the second-most popular buzzword, security issues have been the top concerns of any digital, connected projects out there. 2016 was a "year of hack" around the world, from the (alleged) hacking of the US electionsUS $81 million stolen from Bangladesh Bank, and hacking of airports and banks in Vietnam. All these issues raise the concern of the security of enterprises putting up sensitive information about their business in the cloud, where IoT devices without basic security functions can be hacked within minutes.

Ensuring cyber security is crucial for businesses when they decide whether or not to migrate into the cloud and rely on technologies for operations and sensitive information.

2. Co$t

Cost is another big concern for enterprise IoT adoption, especially in the Small and Medium Enterprises (SMEs) in Southeast Asia. Many of the IoT product offerings currently pose a challenge for SMEs to adopt, especially when the benefits are usually seen in the long run rather than short-term. This is especially apparent in emerging economies like Myanmar, where despite the high potential for enterprise ICT/IoT adoption, the high cost of digital products still poses a challenge to the local companies, prompting them to either seek foreign investments, collaborate, or find localised products that are more affordable - prompting local system integrators and distributors to be active in helping to grow the local markets.

This also prompts another important issue of having a strategic planning when it comes to digitisation and using IoT, in order to cut upfront costs while still benefiting from the new technologies.

3. Sustainable investments & developments

As the IoT buzz continues to ride the waves of publicity, especially from big names like Hewlett Packard Enterprise, IBM, Oracle, Microsoft and Google, enterprises should avoid jumping on the bandwagon without understanding the actual benefits and what IoT can bring to the table. A Bain & Company survey found that 59% of global companies believe they lack the capabilities to generate meaningful business insights from data, while another survey had 85% of respondents saying that they will require substantial investments to update their existing data platform - which can be costly and time-consuming.

Understanding the challenges that the businesses and enterprises face will be crucial for solution providers to offer not only products for the sake of having products, but also be able to offer their clients advice on strategies and plans of how to apply IoT successfully and strategically - depending on each company's needs and requirements.

Businesses in Southeast Asia comprise of many young, robust and innovative enterprises hoping to use technologies to differentiate, expand and produce with high efficiency and productivity. Addressing the pain points and challenges of technologies will allow solution providers and businesses to have better understandings of each other, and help the Southeast Asian IoT market reach new heights.

What is the top challenge that your company is facing with regards to technologies/IoT adoption? Let me know in the comments section.

If you are interested in learning more about Southeast Asia's enterprise IoT markets and connect with businesses across the region about your solutions, drop me a note at [email protected] Looking forward to speaking with you!

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