We recently interacted with Santosh Nair, Head-Analytics, Business Intelligence and Visualization at Lenovo, a global tech company spread across 160+ countries. With over 15 years of experience, he has built and lead complex analytics projects for many Fortune 50 companies in the telecom, retail, ecommerce and manufacturing industries.
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He began by stressing on the fact that Lenovo believes in the concept of different is better and that they constantly innovate to improve the overall customer experience. “We keep customer at the center before launching a product portfolio”, said Nair, who has been heading Lenovo over the last five years and developing competencies in customer analytics, real time recommendations, big data and analytics.
Data driven decisions at Lenovo—from Excel to Tableau and other BI tools
This maker of PCs, thin & light laptops, premium laptops, notebook, smartphones and tablet, has been constantly adding innovative products into its portfolio and for this year, the company’s focus is majorly on smart devices and cloud.
Nair says that a lot of people are using analytics to carry out suitable decision making using data. “The challenge however here is that many a times practitioners do not believe in data or they do not want to adopt new technology”.
Irrespective of this fact, Lenovo has been quick to evolve in terms of its analytics capabilities. Starting the journey of data analytics in 2007 with Excel, the company has invested a lot of money on big data technologies, visualization & BI tools for making data driven decisions. “As we moved forward, we considered various options before finalizing these tools. We adopted Hadoop, Python, Spark, Tensor Flow as we grew in terms of doing advanced analytics”, shares Nair, who currently heads a 25+ member team under him at Bangalore office.
“We started with Tableau in 2014 with about 100 users that had access to the dashboards. Over the years we have integrated enterprise platforms and have started to publish our dashboards online, where people can ask questions in real-time by clicking different buttons”, shares Nair.
By integrating 16 core enterprise serves, it now gives access to more than 10,000 users with access to different kind of dashboards. They have integrated 40 different dashboards into a single master dashboard. “This is a gist of how visualization platform looks like in terms of Tableau and enables decision making at Lenovo”, he adds.
Tableau recently announced the general availability of Tableau 10.3. This latest release would help organizations achieve data-driven insights faster than ever, through automated table and join recommendations powered by machine learning algorithms that simplify the search for the right data for analysis.
“Earlier my team used to send 40+ excel based dashboards, for each country, sub-region, regions and then accumulate the overall findings into a global level. This humongous task would require 5-6 people, which after implementation of Tableau and big data solutions in the back-end has completely become automated. The data can now be seen within a lag of 30-40 minutes, unlike a week earlier”, Nair explains.
That’s not all, it also allows creating different views for different stakeholders. For instance, executives don’t want to look at detailed numbers but only fancy numbers to check if the company’s budget and targets are on track. “In such cases we have executive level view. We have created different views for different levels based on their procurement”, he says.
He also adds that in BI space, nothing is constant. “You are on the move and need to act on different questions asked and find new solutions. Tableau has helped us achieve that. It has also enables the global team at Lenovo to do centralized jobs”, he says.
Overall, Tableau and big data can reduce the cost, increase efficiency and process data in the real-time.
Tableau vs. other BI tools-
“My team uses tableau a lot but it is not limited to just tableau. Different business units within the company uses different technologies based on specific needs—supply chain might use Qlik or marketing team might be using DOMO”, says Nair. At high end at Lenovo, we have tableau, Qlik and domo.
LUCI—the hybrid cloud based platform by Lenovo
Internally at Lenovo, the analytics team builds capabilities in terms of data management, getting data from various sources, doing the automation, visualization, and analytics. The end-to-end analytics adoption at their 30+ business units is different, which depends on the overall business requirement.
Lenovo Unified Customer Intelligence (LUCI), an analytics platform developed by Lenovo’s global intelligence team, is capable of delivering actionable insights from a myriad of global sources in a matter of seconds. “If you want to handle big data and provide real-time decision making, it cannot be done using basic applications alone. We need to have platforms that provide scalability, flexibility and performance. LUCI, is an answer to that and can support all the analytics and BI activities at Lenovo”, shares Nair.
Sentiment Scoring and Voice assistant—AI and machine learning play at Lenovo
Not just on a prescriptive of cognitive platforms, Lenovo is also implementing voice based/ assisted technologies that can provide recommendation to the end customers and can chat with them. “We are using a lot of machine learning techniques and artificial intelligence algorithms to bring this innovation”, says Nair.
As customer centricity remains a major focus at Lenovo, they focus on mapping out ways on how customers engage with Lenovo—throughout the process of making primary research, making a purchase or giving feedback.
Nair explains, “To focus on customer centricity we have created one unique dashboard by integrating 30 different data sources. All these data sources talk about customer feedback which can be from social media, retailer website or surveys. We go through all of this data and run natural language processing to understand what is the theme or how are customer’s sentiment is about Lenovo products”.
They use NLP processing technology to categorize the comment and feedback into different themes and do a sentiment scoring in real-time. This data goes to the dashboard which can be accessed by anyone in the organization with a Lenovo active directory credential.
Based on customer feedback, there are two things that can be done—one is theme classifications or categorization and other is sentiment scoring which can be done from -1 to +1 or -5 to +5.
Future plans for analytics at Lenovo-
Nair shares the following points-
- Mobility- Lot of people are demanding mobility as one of the components, where they can access the dashboards on their laptop or mobile devices. They are demanding more and more customizations to be done on the mobile and we are looking to enable some kind of authorization access so that they can also edit few things and publish.
- Scalability- Second thing is to be fast and scalable in the real-time. The data is always there but there needs to an alert mechanism to set out alerts suggesting if the sales went up or down etc. so that actions can be taken accordingly. Lenovo aims at enabling this kind of process in the decision making in the coming days.
- Voice BI- This is the third plan. There are few executives who are not well versed to go through dashboard and use it specifically for marketing organizations. They fancy numbers and want to get numbers as soon as possible. But there are certain executives who are more data oriented and they want to see everything in a great format. Serving different customers in different ways is the key and Lenovo is working on getting voice BI here.