Operational efficiency is a fancy piece of terminology that every executive, team lead, and employee would gladly strive for. Theoretically, operational efficiency has its foundation in manufacturing—embodying the assembly lines of days past and legends like Henry Ford. Now, operations, and the processes required for optimization, have taken to the mainstream and the core tenets are applied to every role, in every business, within every single industry.
Within technology and software companies you have a natural evolution, and there is a critical inflection point where operational understanding and optimization becomes vital. : Most startups start off with a few people—an idea, a vision, and a mission. As that group heads into the market, typically after having to guess where a product market fit may exist—they must constantly iterate repeatedly until a true product market fit is achieved. Once that magical moment is realized a lot of things happen. The company focuses its messaging and positioning, knows their exact persona and the pain killer-like effects their solution provides, and they start to see a semblance of repeatability. With more customers comes more support needs. With more support needs comes more technical needs. With more technical needs comes the opportunity for more sales, and the cycle continues.
The core driver of all that growth? People—your company’s most important asset. As your organization continues to grow, you will need processes and playbooks. These documents and guides are rooted in data and fact and help you continue to scale. Unfortunately, things change—the market, culture, people, customers—anything that can change will change. There now exists a huge opportunity to keep your pulse on those potential changes and get ahead of any risks to your business, team, even your people by passively analyzing the vast amount of data being generated today.
Data, Data, and More Data
It should come as no surprise that the amount of data being generated today is more than ever before. In fact, data generation is on an exponential growth trajectory and has absolutely zero signs of slowing down. Large organizations have had a huge head start in leveraging this data for operational optimization. They rely on teams of data scientists and data analysts that use several tools for databasing, connecting, analyzing, and visualizing their data in a way that helps inform decisions.
For smaller organizations without the human and technological capital of these large organizations, the opportunity to make the best possible decision at the best possible time are a bit fleeting. People in roles that historically may not have relied on data-driven decision making are now inundated with numbers and data being generated across their technical stack. To get this data in a central location and structure in a way that could even allow for basic analysis would take hours a week. Still even, this skirts the assumption that your colleagues have the skillset to truly derive the most significant findings within a massive set of data. Furthermore, if these companies are a growth stage company,they have goals and requirements that absolutely require making great decision after great decision. Anyone who is aggressively growing without the use of data is both incredibly lucky, but at a huge risk for missing their goals, losing their colleagues, and risking the wellbeing of their people.
The Need to Democratize Data
Since data science and the ability to aggregate, analyze, and act upon the data being generated holds the keys to creating unfair competitive advantages and operational efficiency—it is time to democratize that ability for a broader number of people. In fact, there is a new term for this type of new employee within a company, a citizen data scientist.
Gartner defines a citizen data scientist as, “a person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.” So how do you create a colleague who can conduct both simple and highly sophisticated statistical and analytical analyses, without the previously required experience of a formal data scientist? By leveraging tools that incorporate artificial intelligence, machine learning, and augmented analytics solutions.
Putting the Power of Operational Efficiency into the Hands of the People
Imagine a world in which your employees, management teams, and executive teams all operate from a lone source of truth. Within this source exists all the data from all the tools your company uses to get their (?) respective jobs, projects, and tasks done. With a few clicks of the mouse, team leaders and employees are immediately on the same page without the risk of inherent bias or misinterpretation.
Now take this a layer deeper, what if that same tool could automatically surface impactful recommendations and insights that ensure potential risks can be nipped in the bud? What if your KPIs (key performance indicators) were tracked in real time, and you could get alerts on where you may be tripping up?
Peoplelogic is a People Intelligence platform that companies are adding to their toolbelt to do exactly that. For people managers who are struggling with their team’s goals, their own individual contributions, and a lack of time due to being both a player and coach or for executive teams that need to understand where bottlenecks and process problems exists—Peoplelogic is the solution.
By passively analyzing all the data your teams are producing, Peoplelogic keeps an eye on the overall health of your organization. It makes performance management fair, it democratizes data for every employee regardless of data expertise, and even helps managers get ahead of potential team risks such as burnout, goal misalignment, and overworking.
Peoplelogic is redefining how companies build better teams and how works get done. By empowering every single employee and manager within an organization to make better decisions, faster, operational efficiency has never been easier (or more affordable) to achieve.