Review of 2015 & My Top 4 MDM Predictions for 2016
Happy New Year everyone! I started last year with a blog on the trends we would see in 2015 and beyond. I highlighted eight key predictions on Master Data Management, Data Quality, Data Governance and Data as a Service that we collectively call information quality solutions.
Looking back to what I offered (after spending a lot of time with other leaders in MDM space and my experience working with customers in the different spectrum of MDM adoption), I am happy to tell you that we did a good job in forecasting what was ahead of us.
To name a few things that stood out –
- Many customers are demanding multidomain support in the solution so they can have one system for their current and future master data domain requirements.
- MDM is becoming an integral part of analytics efforts. Many customers I talk to are using MDM as a backbone to big data analytics where the success of the project heavily depends on quality business-critical data about customers, products, locations, and suppliers.
- I see massive adoption of solutions purpose-built for a particular industry or use case. Customers are looking for vendors to build solutions for them on top of an extensible MDM platform.
- MDM on Steroid? Yes, it is. Many customers are looking to supercharge their existing MDM system or use some of the MDM capabilities such as matching on Hadoop to address both volume and velocity of data acquisition from internal and external data sources.
- The market is still solidifying for cloud-based MDM adoption, but as I said in the blog, floodgates are yet to open. The enterprise MDM is very much on premise, but customers are asking for MDM solution to integrate well with the data that resides on the cloud such as Salesforce & Marketo.
2015 was an excellent year for MDM and me personally. As a product marketer, I got to spend much of my time with customers, learning more about the type of business problems they are solving using MDM.
As I analyze the past trends and look into what customer are demanding, here are few speculations about what may be in store for master data management in 2016.
MDM will become critical for driving customer experience: According to Gartner, the majority (89%) of the companies believe that customer experience will be their primary basis for competition by 2016. I predict
- MDM of customer data will continue to be the biggest criteria for MDM adoption in 2016
- More executives will realize MDM is at the heart of providing exceptional customer experience (As observed in Gartner Customer 360 Summit in San Diego last year).
- Organizations will use MDM as a critical tool in their preparation for the competitive battlefield of tomorrow.
MDM will help achieve Mergers & Acquisitions (M&A) synergies faster: According to SpendMatters article, 74% of respondents report M&A plans in the next year. MDM is exquisite requirement for the organizations to ensure the faster realization of M&A synergies. Many companies are finding it hard to integrate a variety of systems resulting from such activities. There is only a handful of organizations that planned ahead their MDM initiatives with M&A in mind. These organizations are seeing their efforts bearing fruits. Although I do not see companies invest solely in MDM to speed up M&A, I believe that it will be a priority for CIO’s & executives planning, carrying out, and integrating data as a result of M&A.
MDM & Big Data use cases will see a substantial rise: 2015 was pivotal year where I saw few organizations leveraging the full potential of MDM by fueling accurate data for their Big Data initiatives. The combination of MDM and Big Data gives rise to a variety of use cases. I would like to highlight three particular types of usage we will see more in 2016.
- Matching, grouping/clustering (ex: Households) will move to Hadoop so organizations can apply MDM techniques to large scale data
- Linking of master data to interactions, transactions, social media data, to drive specific use cases will demand purpose build apps that leverage big data technologies
- Organizations will look for ways in which they can offload some of their existing MDM processing to Hadoop to ensure timely delivery of data.
Customers will demand an integrated solution: Over the years, we have seen that success of MDM depends on other factors such as data profiling, data quality, data integration, data enrichment, Business Process Management and data security. I predict that customers are going to demand a solution that provides all these capabilities as a combined offering.
It is an exciting time to be here for sure. Let me know what you are seeing. Also, check out, predictions from my blogger friend Henrik Sorensen. Henrik has spelled out three ‘gut feelings’ as he puts them, but I have a hint they make accurate predictions.
Please comment.
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Like the phrase “MDM on Steroid” 🙂
Do you think we see the market growing more and more for that rather than traditional MDM.As we talk to customers more and more their is a need to grow that piece in combination with Nalytics platform rather than traditional MDM.
Shweta,
Thanks for comments. I coined that phrase, so I take the full credit 🙂
There is certainly more demand for master data management capabilities that can address Big Data volume and velocity today than it was a year ago. However, the classic use case is still the majority. There are a large number of customers who want to take control of business-critical data about customers, products, suppliers which is smaller in size. However, few forward-looking organizations are not hesitating to start on the big data journey.
I completely agree with your predictions regarding Customer Demand for MDM to encompass a holistic solution. I myself work for a Healthcare Organization that is currently using a Vendor Solution MDM Model as their in-place MDM solution. This solution was implemented about 2 years ago, which has many intricacies and survivorship rules that need to be re-worked due to the Organization’s unique way they input data into their main Source system – outside of additional data feeds they receive from other sources. Due to these growing pains the organization is experiencing with MDM related to Business Rules regarding the Data that were not identified within the solution during initial requirements phases – the organization has had a much harder time receiving a complete buy in from the Business Teams. Much of this is due to the Data Quality issues identified when using the MDM solution as a part of any reporting needed for the organization or external efforts. I myself believe completely in the Master Data Management concept that is backed by a robust Data Governance Methodology customized to each individual Organizations data processes and procedures. When Data Governance is constructively and consistently utilized to drive data quality decisions with the use of Data Profiling, only then can the Data Enrichment process be effective to drive Customer Satisfaction.
The trends mentioned are part of the broader mega trend in data mgmt that has been around since the last 3-4 years.
Great post, I have joined an organisation in which we are going through the process of assessing the quality of our data, and looking at MDM, and remediation of data issues (where it is deemed to be of business value), and it will be interesting to get insight and recommendations from those who have walked the road before.
Prashant, Wondeful article. Recently I joined one organization where they had already MDM process in place. But it is not much accurate. I need to upgrade it. It’s an e-commerce company where people can purchase product and make a payment. In order to take advantage people sometime use different email address, different shipping address & so on. Our web interface will then give a new customer id if data mismatched. So I need to combine them with multiple iteration & need to implement a solution which will give them a single unique id. So that every month we can evaluate that this much % is our new customers and so on. I need to implement in SQL Server 2014. If you can share your experience on this would be much appreciated.
MDM helps me in solving the problems on data analytics
Hi Ronak, firstly got to compliment you on publishing such a wide variety of excellent and topical articles. Most useful.
I’d be interested to get your thoughts on 360 degree view of party and product data. I am looking at this at the moment where we have a desire to implement MDM technologies to satisfy business needs around single party/product view. My thoughts are that MDM will provide the foundational data but exposing the actual view to consumers will be done through some consuming tool whether that be CRM or something surfaced through a BI layer. Interested to get your thoughts.
Thanks.
MDM helps us more in future to solve the data analysis problems. Your article is great and informative.
[…] been predicting this one for a while now. It turns out that I'm not alone. As Prash Chandramohan writes, organizations are beginning to apply MDM techniques to unstructured data. This may be as simple as […]
another good one Prasanth,
based on my observations, most of the organizations think MDM is bulky & expensive solution because of the record level licensing model and complexity to upgrade with the customized solution. during our assessment for next generation MDM, we are considering the cost effective solutions like Cloud with easy integration with third party data vendors which avoids million dollar upgrades and provides stability. This helps on cost / C360 solution with CRM systems.
Thanks,
RK