February 18, 2021

Top 5 Ways in which Data-Driven Decision Making will improve your Procurement Profitability

Data driven decision making (DDMM) – is a process which involves collecting data based on the measurable goals or KPIs. DDMM analyses patterns and statistics from these insights and utilize them to develop strategies and activities – which will help the business in number of areas. Fundamentally data driven decision making means working towards key business goals by leveraging verified and analysed data. 

To extract genuine value from your data – it must be accurate as well as relevant to your aims. Collecting, extracting, formatting and analysing insights for enhanced data driven decision making in business was once an all-encompassing task that naturally delayed the entire data decision making process.

"Information is the oil of the 21st Century, and analytics is the combustion engine."   – Peter Sondergaard

The gold which the data scientists have been mining falls into two categories: Qualitative and Quantitative and to make a data driven decision, both the types are important and critical to understand. Qualitative analysis focuses on data which isn’t defined by numbers or metrics like interviews, videos and anecdotes. And quantitative data focuses on numbers and statistics. The median, standard deviation and other descriptive stats play major role here.

So, now that we have explored – the meaning and type of decision making in business, it is time to consider the reason why data driven decision making (DDMM) is important. 

Top 5 ways in which Data-Driven Decision Making (DDMM) will improve your Procurement Profitability

The importance of data in decision lies in consistency and continual growth. It will enable the companies to create new business opportunities, generate more revenue, predict future trends, optimize current operational efforts and produce actionable insights. 

  • Collect Relevant Data 

Gathering the data is as crucial as asking the right questions. Like for SMBs or enterprises – data collection should begin from the very first day. Jack Dorsey, founder and co-creator of Twitter, one shared, “For the first two years of Twitter’s life, we were flying bling, and we were basing everything on intuition instead of having a good balance between intuition and data. So the first thing I wrote for Square is an admin dashboard. We have a very strong discipline to log everything and measure everything”.

Implementing a business dashboard culture in your company is a key component to manage properly the tidal waves of data you will collect. Also, it is important to gather relevant data.

  • Presenting the data is a relevant way

Mining the data is ok, finding out the relevant data from it is also ok but what about creating actionable insights? Like how you will present your discoveries and communicate through your data. You must make sure that your acumen doesn’t remain untapped and dusty, and it will be used for future decision making. With the help of the data visualization software, you can keep your collected data in a manner. 

  • Unbiased Behaviour

Most of the mental work we do is unconsciously – which will make it difficult to verify the logic we use when we make a decision. At times, even we can be guilty of seeing the data we wish was there instead of what’s really in front of us. Running your decisions by a competent party who doesn’t share your biases is an invaluable step.   

Democratizing data empowers all people, regardless of their technical skills to access it and help make informed decisions. Even this is done through innovative dashboard software, visualizing once complicated tables and graphs in such ways – that more people can initiate good data driven business decisions. 

How to overcome biased behaviour: By simple awareness, by collaborating and by seeking out conflicting information. 

  • Define Objectives

To get the most out of your data teams, companies should define their objectives before beginning their analysis. Like, first of all set a strategy to avoid following the hype instead of the needs of your business. Define clear Key Performance Indicators (KPIs). There are various KPI examples you can choose from, don’t overdo them, don’t put the irrelevant ones. Only concentrate on the most important ones within your industry. 

  • Solve the unresolved questions

Once your goals, objectives and strategies are set – after which you will need to find the unresolved questions, which will help you reach the goals. Asking the right data analysis questions are as important as finding the relevant data for your business.


It is totally true that by harnessing data in the right way and measuring your success – you stand to improve your procurement and propel your business to new and exciting heights. Now when you have all the spices in your closet, the best way to cook delicious food is to apply the correct methodology with the permutation and combination. For maximum success, you should avoid taking the wrong approach to data driven business decisions at all costs. A failure to do so will lead to making choices with your gut, biases, or fostering a poor data culture within your organization.