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Achieve more with the Right Innovation and Integration

Jin Zhang, Senior Director of Product Management, CA Technologies

Jin Zhang, Senior Director of Product Management, CA Technologies, Jin Zhang is Senior Director of Product Management at CA Technologies where she leads the product and design team for Analytics in the company’s...  More >>

Trends in the Big Data Landscape

One of the trends that is up and coming is the growth of domain-specific or special-purpose clouds. We are seeing an increasing amount of open-mindedness and adoption because it makes a lot of sense from a monetization point of view. For example, focused use cases allow optimization of cloud resources; ecosystems of similar domain generate cross-industry learning and larger data pools; joined marketing and branding efforts allow smaller players an easier entry into the space. I have seen this trend more in Asia Pacific but it is growing in other geographies as well. The significant impact it has on Big Data is that the analysis of Big Data has to be more domain-aware. For example, the word “post” means something quite different for an e-commerce use case verses a government service portal. This trend will push Big Data beyond the ingestion and searching/indexing phase, and focus it more on the analysis stage including machine learning and natural language processing.

  People must remember to focus on the problem to solve, rather than focusing on Big Data itself  

Integration is an Important Factor

One major technology challenge involves overcoming a lack of integration that results in increased complexity, especially in enterprise software. There are so many vendors and they all do things differently. Even the same vendor can have many different products and solutions and yet they often don’t all talk to each other. I have heard from our customers that their biggest wish is for data to be re-used and systems better integrated, so that they do not have to involve 30 people from five locations to run 10-hour triage calls. Technology vendors are challenged with the balance of focusing on solving a specific problem verses investing in pre-existing integration of common tools. This is a tough challenge but definitely a differentiator that is worth pursuing. One good example is the emerging vendors who focus on providing Big Data solutions involving the construction of data lakes where data points for multiple tools and solutions go into the same data repository. With this, at least one side of the coin gets to “co-locate” with the other side – even if the next step of collating them together is still a big challenge.

For CA Technologies, we are integrating data into our cycle of serving customers and creating software that is more intuitive, real-time, and fact-based. None of these can be made possible without the support of technology. One example is our customer success journey. We were able to leverage data to pinpoint exactly the area where customer delight could be significantly improved, and based on that insight we adjusted our process and customer service flow accordingly. This resulted into significant increase of our NPS (Net Promoter Score).

Focus on the Problem

People must remember to focus on the problem to solve, rather than focusing on Big Data itself. What I mean by that is that whenever there is a new buzz word, people tend to gather with the crowd and tie whatever they are doing to the hottest trend. That distracts from a true problem-solving approach that serves an enterprise. At CA we focus on investing our time with customers to understand the true problems. We ask the question from many angles, and sometimes repeatedly, “what’s the real problem”, “how do you know that it is a big problem”, “what happens when the problem is resolved”, and “have you gathered any data to measure the impact of this problem.” If it turns out to be an integration issue, we then address the integration issue. If we discover a problem can be solved with a smaller-than-expected customer investment, it is solved with a smaller investment so that customers can see their ROI quickly. We do not come in with the big bang approach, and we understand that not every problem is a Big Data problem. That happens to be an important takeaway from serving our enterprise customers.

Nurturing an Innovation Culture

Innovation is hard, and it is especially hard within an enterprise. Focus on the culture, then hopefully ideas will follow. Enterprises today rely on innovation to gain the competitive edge.  Innovation can happen in many areas, including new product ideas, discovering a new need, an interruptive way of solving an existing problem, or new methods and process that brings customer delight. While the executive team cannot possibly act on every innovative idea in all areas, nurturing an innovation culture in your organization would allow the truly great ideas to be surfaced and executed. It is about rewarding risk-taking, accommodating the wild goose, and guiding the innovation pipeline by sharing a clear organizational vision and goals. I was recently reading the book “Originals” by Adam Grant and he discusses how the best way to identify innovative ideas is not by listing to a set of evaluation criteria, but by thinking of your own innovation right before listening to the pitches. This type of practice is critical for C-level executives because it gives them the innovation spark needed not only in Big Data, but also in IoT, mobile, wearables, and many more rising areas.

tag

ROI

Enterprise software

Natural Language Processing

Machine Learning

IoT

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