How to Benefit from Data-Driven Decision Management
Data-driven decision management (DDDM) is a strategy that supports extracting as much data as possible to make better business decisions. The ultimate success of a data-driven approach depends upon the quality of the data gathered, the context surrounding the data collected, and how effective the analysis and interpretation.
As a concept, this is easy to understand. If you have more data, you should be able to make a better decision. There are many choices we make. Some might have been different had more data been available. For example, the decision to drive to work along your normal route might have been different had you known a car accident had just occurred, blocking lanes and causing delays. With this insight you might have taken an alternate route.
The same can be said of business decisions. Availability of the right data at the right time can have a profound impact on how an organization’s decisions are made, ultimately impacting productivity and profitability.
Living in the Age of Data
I have a fond memory of a classic Dustin Hoffman movie, The Graduate. In it he plays a recent college graduate under scrutiny on what he will do next with the rest of his life, now that he has his college degree.
A classic quote from the movie is one of the conversations he had with one of his parent’s friends, Mr. Maguire, who tells him, “There is a great future in plastics.”
Had that movie been filmed today, Mr. Maguire might have instead suggested “There is a great future in data.”
Data is everywhere, and is impacting more of our lives every day. The problem used to be finding the right data. Today, the challenge is too much data, and non-relevant data. Much progress has been made.
Extracting the Greatest Value from Data
Manufacturers have had success recently unlocking the value of data from their operations. This transformation has led to more effective process improvement, greater success in extracting waste from production processes and an ability to respond faster to recalls or other product quality consistency issues. Not only faster, but more precise.
Marketers have embraced digital marketing to drive significant return on investment by capturing browsing data to identify what websites prospects have visited and what products are being searched for. This is why banner ads start appearing the next day for exactly what you were previously searching for. Personalized direct mail now gets delivered with specific, unique offers specifically targeting you.
A recent partnership announcement between Salesforce and Google plans to leverage sales and marketing data to help improve efficiency and sales productivity metrics by sales team using a combination of these products.
Sales professionals now regularly use LinkedIn to understand the profiles of prospective customers to learn more about what their interests are, where they used to work and what their alma maters are. With this information, a more personalized selling approach is possible, helping to increase the chance of a successful sale.
Sales managers now have access to much greater amounts of data on how their teams are performing – with applications such as Prodoscore – that can help identify best practices and quantify process improvement and productivity gains. This knowledge become sales performance intelligence, which can then be shared with the rest of their teams to elevate overall sales team productivity.
Adopting Data-Driven Decision Management
Most agree that information is highly valuable for decision making. According to a survey conducted earlier this year by BI-SURVEY with 728 participants, 48 percent agreed that information is highly valuable for decision making today. That figure is forecast to grow to 67 percent.
Yet with all the agreement on how valuable information is to make better decisions, only half of all business decisions are data-driven. Further, only half of the available information in organizations is even considered for decision-making. Reading between the lines, it would appear there is a huge amount of upside for businesses to start getting more serious about their data strategy, and what can be done now to achieve improved results.
The following is a short list of high level tasks that can be done today, which will then result in becoming a DDDM organization.
- Address and improve data quality – consider what processes are in place that lead to data collection within your organization. How is accuracy monitored? What periodic reviews are done with the data collection process, and how is it tested? By incorporating a review and audit of your data quality and the processes surrounding data collection, the quality of your DDDM will improve.
- Lower the cost of access to information – do you know what is involved in collecting data, and what it costs to acquire? Do you use third party sources? Or, is your customer base sufficiently large enough that instead, time and effort should be invested to curate that data? Cost effective strategies to expand access to data will translate into improved decision support in the future, with better decisions being the result.
- Improve the way in which information is presented – how is data shared within your organization? Is it readily available across the enterprise? Role-based access control can be used to keep sensitive data restricted to just those who need it. Ensuring the rest of the data is readily available to all others – and can be accessed easily and accurately – will amplify any benefits possible with a DDDM strategy.
- Make information easier to find – this concept is all about how data is indexed, and what context is part of the data collection process. This “meta” data can then be sued to make information easier to find and to connect disparate data together, as applicable. More data that is available and can be used translates into further benefits and better decision support.
- Increase the speed at which information is made available – data is quite often time sensitive. Old data or data presented days or weeks past when it could have been used won’t do much to help with decision support. The “holy grail” is access to “real-time” data whereby information is quickly made available as collected. To establish such a strategy, data must be collected “clean” or without a need to audit or correct, ensuring accuracy is correct. Clean data can be used instantly, in real-time to support real-time business decisions.
- Raise awareness of business intelligence at senior management levels – in order for an organization to embrace a DDDM strategy, it is critical to have executive buy-in so the strategy can be implemented as an enterprise decision. Just as the weakest link in a chain will cause it to break, so too is the case with embracing DDDM. Data must be made available across functions, geographies and roles throughout the entire organization to fully capture the potential benefits of becoming a DDDM organization.
- Foster a collaborative style of decision-making – as a final step in your DDDM maturity, once clean data is cost effectively collected, accessible and available with context, to readily access and use as part of a decision process, the next step is how to evolve as an organization. Here, the transformation is not necessarily tied to the technology, but instead, to the culture on how it is used, which might have required changes to processes to encourage greater collaboration, and hence, better and more informed decisions. Once this threshold is achieved, there will be no stopping what can be done by your organization!
The availability of data today has reached unprecedented levels. The potential is enormous with what can be extracted from this data, which can be used as intelligence to more informed, smarter decision making.
Organizations with access to the right data – and an ability to use that data as an embedded part of how business processes are executed – stand to benefit significantly in the digital age we now all live in. The only question is whether your organization will be in the lead with this strategy, or your competition.