Ramesh Dontha is a passionate business enthusiast, who is well versed in the realms of Big Data and Data Management, which are the key drivers when comes to digital transformation. We live in a digital economy where content is produced in different variety and at a higher volume, where determining the veracity of data is the biggest challenge. According to Ramesh, data holds a herculean value when corporations treat it as an asset and use this powerful tool to garner business value.
Mr Ramesh is currently engaged as the Managing Partner ofDigitalTransformationPro.com, a professional services organization that educate, enables and empowers organizations to cope with the dynamic and disruptive digital transformation.
Let me explain what DigitalTransformatioPro stands for.
More than a professional company, I would call it a media company where we would like to educate, enable and empower both people and organizations with knowledge on digital transformation topics related to data, data analytics, few of the latest trends like artificial intelligence, machine learning, etc
Prior to DigitalTransformationPro, Ramesh has logged two decades of experience with major technology companies such as Intel Corporation, where he delivered high impact initiatives in data management, data strategies and data governance.
Value of data by Ramesh Dontha:
As a business or just as an individual, we generate data. Data comes from many sources. If you let it there and do anything about it just going to be a waste. Instead if you treat it as an asset the same way we treat people as an asset, and try to dig into it and find what’s in the data, analyze it a bit more and find what intelligence we can find out of the data and then use it to make informed decisions to penetrate to a new market. The fascinating part about data is that the intel you gather can be used to outline and implement new strategies with existing market, grow revenue, find ways to reduce expenses. Then data as an asset has a tremendous value for a business.
Q & A
Ramesh Dontha: There is a general consensus that big data is primarily defined by 3 ‘V’s which are Volume, Velocity, and Variety. Big Data is large volumes of data (in peta bytes) generated rapidly (primarily because of social networks), and comes in many varieties (structured, unstructured, text, videos, emails, images, audio etc.). The regular data or sometimes called small data is smaller in volume, primarily structured (that can be handled by relational databases) and deals with organizational operational data (business transactions, ERP etc.). Leading companies are realizing that big data has a lot of valuable information that can help them grow revenue, open new markets, reduce costs, and deliver better customer service if they can dig into these volumes of data (mine the data) analyze the data to help them make smart decisions.
Ramesh Dontha: That is probably the most significant challenge. Given these large volumes of all varieties of data being generated at a rapid pace, how can organizations manage it let alone analyze it? In my opinion, data can only be of value if it can help realize business strategies. Whether it is big data or small data, the business basics are the same. So the first thing for organizations to do is to have a solid understanding of their business strategy and goals. Is it to penetrate new markets? Expand customer base? Generate more sales with existing customer base? Reduce operational expenses? Once they are clear on strategies, figure out the pain points or road blocks relating to data that are preventing them from realizing those strategies? For example, one pain point could be that there is no single source of truth for all of their existing customers. If that’s the case, first try to manage the customer data by focusing on creating a ‘master list of customer data’. Clean and enrich that customer data so the organization can then run analytics to figure out their top customers, percentage of sales to top customers etc. It is just one example. It could be about products, financial information, or supply chain.
Ramesh Dontha: A startup company might have different needs compared to an established company. In some ways, startups have an advantage over established companies as they can start from scratch and embrace latest tools technologies whereas established ones need to deal with legacy systems and processes. Startups are probably savvy about managing and dealing with data generated from social networks.
For eg: In terms of an eCommerce business, you have wide access to your consumer’s data. Every time a prospect interacts with your website he/ she leaves traces and bits of information related to their personal profile. Be it their email id, name, company details, etc. The value is derived when an entity as its own tries to piece together these bits and pieces of information (with the dexterity and proclivity of solving a puzzle) and ends up creating a customer dimension. Data in its structured format can leverage knowledge which portrays a wonderful picture of the customers. Which then can be categorised into different stages in a buyer’s journey. Here the data at its core helped you to create customer profiles and then the customer profiles are categorised into different stages in the buyer’s journey. Here the biggest advantage is that the data has helped you to identify your customer’s position in a buyer’s journey and now with the insights you collected, you can nurture your prospects down the buyer’s journey and converting them into loyal customers or even to the best, a brand advocate.
Ramesh Dontha: Six step data quality framework is somewhat of a general guide to go about data quality process. The steps are: Define Business Goals, Assess existing state, Analyze assessment results, Develop improvement plans, Implement proposed solutions, and Set Up a control process. As you can see, it starts with business goals. I described this six step process in detail here in this article “Data Quality Simple 6 Step Process“.
Earlier for the question Value of Data, I have mentioned that data is there unless you can trust the data you can’t really do anything. Trusting the data comes from making sure that the data is of high quality. For the data to be of high quality, we created a framework of 6 steps process to make sure the data you have is maintained of high quality.
Step One: Defining Business Goals
Data has no value or meaning unless you use it to serve a business (a purpose). In that case first you want to define a business goal. Say for eg: You are planning to expand to a new market or improve the service quality of existing customers.
Step Two: Assessing the existing stage of the data
Say customer records. Ask the question of whether I have complete information of the individual customer’s. Name, address, etc but few information’s are missing. So look for a duplicate of the customer data. In most cases you have multiple records for the same customer, so you access the existing customer data.
Step 3: Analyze the data
In this stage you will analyze the data, say you have 99% unique customer records, remaining one percentage duplicate. And of all the unique records you have, Address is not verified for about 40%, but 60% have a verified address. That gives you an idea of what you need to do to make sure that the data is of high quality.
Step 4: Develop an Improvement plan
So you Assessed it analyzed the data, based on that now you know that 40% of the address needs to be verified. The uniqueness of the data is there but the completeness of the data is not there. So that’s where we need to fix.
Step 5: You Implement the proposed solution
Taking the example of the address itself, how are you going to complete the address. You may need a third party service provider that will provide you with the service, that will provide you with the addresses that you can fill in for the existing customers. those are the kinds of activity you need to do at this stage.
Step 6: Making it an ongoing process
On a quarterly, monthly basis you need to go back and check the data quality and based on the goals you have set, you need a 100% address validation done on the records.
Ramesh Dontha: Digital transformation has become the main component of business strategy for many companies. Key technologies driving this are Cloud computing, Big data and analytics, smart machines and artificial intelligence, Internet of Things (IOT evolution, and Augmented / Virtual Reality to name a few. Of these, I believe cloud computing and data analytics are having the biggest impact on digital transformation and are applicable to almost all companies. Main barriers to digital transformation are not new but barriers to any transformation. First and foremost is organization culture with respect to their adaptability to change. User experience is another barrier as a poor user experience significantly holds back transformation. Collaboration or lack of it is another significant barrier. To overcome these barriers, my advice is to start small and build on it.
Ramesh Dontha: Internet of Things has been a huge influence on digital transformation more recently. There is a lot of buzz about IoT but companies are still trying to figure out its overall impact. I believe IoT’s influence is with respect to the ubiquitous nature of ‘IOT devices’ (sensors, speakers, cameras etc.), the amount of data they generate, and the ‘intelligence’ associated with these devices. I believe IoT’s influence will only grow and organizations need to include them in their digital transformation strategies.
Ramesh Dontha: I have a different take on this. I believe that there are multiple approaches to digital transformation and organizations need to figure out what is best for them based on their culture, legacy, available resources etc. Small increments of digital upgrades may be OK if that’s what their organization can handle. Many times, big-bang huge digital transformations fail as they may be trying to tackle too much too soon. I’d advise companies to figure out what is best for them based on factors such as cultural, resources, goals etc. but they must embrace technology evolution and do something.
Ramesh Dontha: It is a true statement that rapid innovation is a key enabler of digital transformation and organizations that creatively exploit that rapid innovation has grown substantially. If you look at some of the latest technology companies such as Uber, AirBnB, Flipkart etc, it is clear that they creatively innovated and used digital technologies as a core of their business to grow at an astronomical pace. They are disrupting existing markets and creating new markets and all of that is possible only with rapid innovation.
Nishant: Can you explain what digital transformation means for today’s business?
Ramesh Dontha: Digital transformation should be the core component of any business strategy. Today’s businesses will either thrive or dive into oblivion depending on how they embrace digital transformation to grow their business. It’s as simple as that.
Initially, the digital transformation was a trend, Now it’s no longer a trend. It’s the core component of any business strategy. How can you use the digital technology whether it’s a cloud computing, whether its data analytics, etc? Make it a core component of your business strategy. That’s why digital transformation is extremely important for all businesses to understand and take advantage of it.
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