Teradata conducts an annual survey around analytics. This came out a while back and was summarized in a press release - More Decisions, More Complexity, More Data: Teradata Survey Validates Global Phenomenon. There were some conclusions in this report that I found fascinating and so I thought I would blog about it. I picked the best time - it is a while since the press release so it's not timely and it is too early to get the printed survey from Teradata. This was not designed to be inconvenient, it's just when I got around to it.
So, some key findings and my thoughts about them:
- Data volumes are increasing massively - over half of respondents saying that data volume is doubling or tripling over the previous year To me this means automate or die. Data volumes are going nowhere but up and it's going to get harder and harder for people to effectively use all this data. One of the great things about computers is a much greater capacity for managing volume so why not turn all this data into insight/actions that can be executed automatically?
- One common response to this extra data is to add staff I suspect most of this was to handle the data management itself but if companies are adding staff to try and process the extra data, that's not going to scale. This data is only going to be useful if it can be applied to business problems and the volume and volume growth mean that this application will have to be automated.
- According to almost 40 percent of respondents, front-line staff is increasingly making critical business decisions A core concept of enterprise decision management is the empowerment of front-line staff to make analytically-sound decisions but to do so without requiring them to become analytic sophisticates or BI tool experts. If front-line staff are making customer treatment decisions then they are likely NOT making them as well as they could because they don't have the analytic skills, or time, to analyze what all your data is telling you. Why not automate this insight and deliver decisions to the front-line so they can focus on customer relationships?
- Ensure that the entire organization consistently executes against strategy One of the biggest problems in this is the need to keep some elements of strategy, and much customer data, confidential or at least tightly controlled. By using this strategy and data to inform automated decisions, you can implement the strategy in a flexible, high-performance way without requiring everyone to know the strategy or see the confidential data. True strategic alignment.
- The top five casualties of poor decision-making are customer loyalty, company reputation among customers, profits, company productivity and customer service The clear problem of poor decisions is the impact on your relationship with your customers. Making sure that customers are treated correctly and that they have a good experience, one that won't cause them to leave, is key. Integrating analytics and process will deliver this.
- The importance of real-time information is a five-year trend, and this year, eighty-five percent of respondents said that decision-makers need more up-to-date information than in the past So more and more people need to take more and more decisions with more and more data in less and less time. Hmm, sounds like these people need to automate some of this... As a Teradata executive said "when you have the customer on the phone or in front of you, or you have a truck in the loading dock, you want to make sure that the right data is available so that the best decisions can be made on the spot," . The data is interesting, the decision is what matters. Helping people make decisions is one approach (BI) but automating these decisions so they can be managed and improved (EDM) is another. EDM will let you capitalize on the customer insights that are now available to you and help address some of the latency in getting from data to better customer decisions.
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