6 ways to manage your data – and team

Decision making comes with its challenges as it’s part of a process of nurturing a variety of perspectives, usually by encouraging discussion and debate. However, when competing points of view are left unmanaged, it can easily – and without warning – digress into an unhealthy conflict. Proponents are often passionate about their views and become blind to certain, inconvenient, facts.

Today, data has become a reliable arbiter for such debates. This is why business intelligence (BI) has emerged as crucial to the decision making process. BI provides actionable insights that are based on numbers. A growing number of organizations are recognizing its value. In 2016, 73 percent of businesses increased their analytics capabilities.

Becoming data-driven doesn’t necessarily require you to create a dedicated team to focus solely on BI. The rise of self-service BI and modern tools has made analytics easier to implement and integrate into your ways of working.

Here are 6 ways you can manage data and help drive your team.

1. Invest in a robust BI service

Previously, BI was only accessible to large organizations. Data projects required substantial investments in infrastructure, software and people. However, with the rise of cloud-based analytics and BI services, even small to medium enterprises now have the means to be data-driven.

Many online businesses already benefit from freemium services like Google Analytics which enable them to track site performance and visitor activity. Those looking to consolidate business data from multiple sources do well looking into end-to-end service providers such as CoolaData, a business intelligence and behavioral analytics platform for digital businesses.

Writing about the challenges many early stage startups face, Guy Greenberg, the cofounder of CoolaData says business intelligence is especially important when you think you don’t have a concrete need for the data.

“The insights you receive from analyzing those first marketing campaigns as the behavioral analysis of the first users contribute greatly to product optimization and successful marketing.”

Partnering with a sturdy service is vital to your BI efforts. Data has to be gathered, stored, crunched, and analyzed before actionable insights can be generated. This is why traditional BI required resources to implement. Thanks to cloud computing, end-to-end BI systems now offer these processes as part of their services. These also feature collaboration and social functionalities to allow teams to jointly work on data.

2. Break down siloes

It’s not uncommon in certain teams to become territorial over their focus areas. When this happens, organizations can suffer from the silo effect. Information stops flowing and collaboration across the organization becomes a challenge.

BI helps curb this through transparency. BI systems consolidates data from multiple sources. Team members can then study and review the data through the BI system’s collaboration functions. It’s easy to see if performance indicators are being met. Because of this, there’s little chance to distort the real status of efforts and fudge the numbers. Ventures, especially those still building up the business, should have little room for such issues.

3. Acquire data skills

Some teams can get caught up by the novelty of implementing new efforts. They may overlook the need for developing new skills to be able to apply the best practices required by the effort.

It helps to develop data skills in your people even if these BI services are self-service and are designed for use by non-specialists. In fact, data-driven organizations consider analysis skills as a fundamental to their staff’s capabilities. Aside from analysis, people also have to be able to communicate their observations and insights.

It also wouldn’t hurt to actually bring in data specialists into your company. These people can help identify potential biases and errors and contextualize reports. They don’t have to be part of a dedicated data team as many data experts can be deployed under marketing and business development functions.

4. Relate to your context

One of the pitfalls in implementing BI efforts is worrying about each and every piece of information that gets to the system. This could be overwhelming and even compel people to exaggerate every negative trend.

For example, data shows a dramatic drop in resolved support tickets this month. Without context, some may assume that the support department is doing poorly. However, what if a new software update was just released two weeks ago and was designed to address issues that users previously complained about. There must be a correlation between the release of a patch and the number of complaints.

This is why analysis becomes a crucial element of BI. Numbers shouldn’t simply be left to point out the “what” but they should prompt a deeper exploration of the “why” and “how.”

5. Decide on how to decide

Transparency does come with a few caveats. As more people get to have access to timely information, the more likely they are to demand quicker decisions. As such, organizations should be clear on people’s roles in the decision making process. Sloan School’s Michael Schrage proposes the use of the RACI framework to clarify roles such as who is responsible, accountable, consulted, and informed.

Implementing data projects can also overwhelm organizations with the amount of data that’s present at any given time. In a survey by Longitude Research, 32 percent of organizations claim that their big data efforts have made it worse for them. Analysis paralysis does happen. Decision makers may obsess about reviewing data over and over to make an infallible decision until no decision is made. To combat this, decision makers have to focused on moving things forward.

6. Drive action through insights

Decision makers must not be afraid to take action. Realizing how trends correlate to each other could show you what interventions are needed but you must still decide and act on it accordingly. It is only through action where BI realizes its value to the organization. You should also look into proper segmentation of data, such as closed-loop analytics, which allows you to close the loop “between the data collected by marketing and the data collected by sales.”

While informed decisions often lead to the desired outcomes, there will still be some probability that you may not be satisfied with the results. Data simply minimizes those odds but not eliminate them. Accepting this reality could help overcome analysis paralysis so that organizations can quickly work towards trying out solutions.

That said, the transparency that BI brings can be framed in a positive way. BI systems now also feature dashboards where business can set the indicators they want tracked. Try integrated dashboards that aggregate data from your enterprise and social application and BI systems.

These dashboards can be broadcast in physical screens around the workplace to let everyone know how the business is performing in real time.

Transforming your business in a data-driven organization can be challenging but the benefits, when realized, can make all the difference. BI promotes transparency, a free flow of information, and better decision making. It helps curb bias and can be used to get everyone on the same page. When everyone gets on with the program, the business then gets a better chance to achieve its goals.