Using AI for customer service in your company is a definite method to save time and money. If you’re like most business owners, you’re constantly searching for fresh, creative ways to improve your enterprise. We’re here to inform you that improving AI customer service is a simple and rapid win.
If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
How can AI-powered executive summaries help with software delivery? A good question and it has a fairly simple answer. Endless Modernization by the Standish Group sums it up succinctly, “The root cause of software project failures and challenges is slow decision latency.” This is very important because most sources agree that ~70% of software projects are challenged on time, budget, and/or specifications. However, AI reporting has several mechanisms to enable near real-time decisions. Plus, this trick isn’t just for kids er… um… executives, AI reporting is useful for all software development stakeholders to squish decision latency, but also dramatically improve organizational alignment
Executive dashboards provide decision-makers with KPI reports for their most important business objectives and organizational health. They work like executive summaries with nice color-coded charts and graphs while also making it easy to dig deeper for more granular information. They are customizable as each CxO and stakeholder needs different data.
Most executive dashboards capture data but they leave the analysis to you. That analysis can take time to dig through the data to determine the root causes of problems, what can be optimized, and by how much. The time spent analyzing delays decisions. In software development, time is very expensive. Moreover, the longer a problem is allowed to persist, the more likely it is to compound in cost, whether it is excessive code complexity or the cost to fix bugs.
We reference this simple diagram frequently as it directly illustrates the “root cause of software project failures.” If you can solve the decision latency issue you solve a lot of problems faster – and this brings us to the role of AI.
Gitential’s in the process of transforming its analytics dashboard into an AI Assistant because AI reporting squishes analysis latency into an almost instant, real-time process – about as fast as you can formulate questions. For starters, this gets you into the decision-making process faster. AI also provides a number of mechanisms to radically accelerate the decision-making process, too:
Again, AI reporting is useful for all stakeholders, not just CxOs. In software development, this extends to BI analysts, HR managers, Engineering Managers (encompassing DevOps and DataOps), and individual developers, too.
So, it’s hard to say that AI makes it possible for everyone to make decisions instantly. In some cases, it can, like in convincing HR or Engineering Managers to start a training program to skill up existing developers vs. hiring more. In a lot of cases, decisions require approval from other stakeholders. A BI Analyst might find a project or feature to have a low value or ROI and that resources allocated to it would more optimally be applied to a different project or even pushed to a different team or vendor. This could require C-level approval.
When a stakeholder does require approval or agreement from other stakeholders, it’ll be necessary to share the data and discuss it like normal. AI helps here with Next Best Actions making it easier and faster to prepare proposals, action plans, risk assessments, and cost performance analysis. Then, it’s up to your regular organizational processes – whether to send reports on the fly via email for the approving authority to review or discuss them in your next meeting.
For the engineering side of the implementation equation, Agile and other best practices provide ample opportunities to rapidly initiate action:
Having addressed how AI helps to squish decision latency to resolve challenges faster, let’s turn to how it helps calibrate organizational alignment. Executives have the task of navigating their organization to continuous profitability, growth, customer satisfaction, and inspiring objectives like organizing the world’s data, colonizing Mars, or mining asteroids.
Say what? Well, Google and the world’s two richest people didn’t get to where they are by doing what they knew they could do…
So, let’s interrupt this post with Dr. Benjamin Hardy’s talk on 10x’ing. He’s speaking in personal terms in this video, but the same applies organizationally. As an executive or startup founder, you might set a goal of improving revenue from $1 million to $2 million this year. In doing so, everyone will be targeting what’s needed to accomplish that. Conversely, the 10x concept pushes you to align and motivate everyone to make a Moon Shot – and generate $10 million.
With inflation these days, that’ll be a lot like making $1 million, so some aim for a Mars Shot to make $100 million… Being facetious. Sorta.
Without organizational alignment, a BI Analyst seeking to cut costs could suggest downsizing the development team to make this quarter’s balance look better – only for the HR Manager to rehire or recruit new developers in the next quarter or two. Similarly, the HR Manager might be hard-pressed to properly vet them in the interest of getting some warm bodies. This leaves the engineering manager in a pickle or ten while individual developers pick up on the chaos and leave for greener pastures with fewer earthquakes.
Aligning everyone to the same objective and metrics corresponding to their role helps assure no one’s working at cross-purposes. The BI Analyst can determine optimal team sizes and commitment to each project to improve value and reduce waste for the long term. Less recruiting lets the HR Manager focus on issues of training and retention. Engineering Managers can better optimize efforts for stable teams than ones in constant flux. All of these efforts apply to an environment that’ll keep developers around longer and steadily improve their personal performance.
Once an executive or manager defines clear and specific objectives, the entire organization can bring laser-like focus on two things – what they need to do to achieve them, and how they can help others achieve them, too. This cycles back to executives and managers with what they can do to help their team accomplish their goals.
At this point, it may help to take a look at how this works organizationally for several stakeholders. This objective is pervasive, suffice that it could be how to reduce defects, how to increase customer engagement, or any number of other objectives.
| Objective | Increase profitability organizationally or by project |
| Core KPIs | Cycle Time and Cost Performance – doing things faster, better, and cheaper. |
| Executive | Ideally, executives should:
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| BI Analyst |
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| HR Manager |
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| Engineering Manager |
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| Individual Developer |
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Decision-makers have essentially 3-4 options – approve, decline, or ask for more data. Delaying a decision is a decision, suffice that some actions may have dependencies or are of a secondary priority. With everyone in your organization having access to “Insights On-Demand” – they’re able to get you the data and their action plans on a vastly accelerated basis.
While developers can only ever become 100% efficient, there is (as yet) no ceiling when it comes to productivity. According to Stripe’s Developer Coefficient, the average team loses about 32% of productivity due to inefficiency. In effect, for every three developers, you’re getting the throughput of two.
Implementing Continuous Integration / Delivery / Deployment can radically enhance productivity – each progressively adds automation to the SDLC. Puppet indicates teams practicing Continuous Deployment have lead times 2,555x faster than manual teams – that a CD team can do in an hour what would take a manual team up to 6 months! They also deploy 200x more frequently and have a 24x faster MTTR.
Your decisions and assistance are invaluable and often of strategic importance. Faster data-driven decisions save time, help optimize developer hours to better meet project requirements. AI helps you address all three challenges (cost, schedule, and specs) in one fell swoop. If today’s tech giants got to where they are mostly without the benefit of AI, it’s worth looking at what you could do with it.
Alpha Centauri is only 4.4 light-years away, and while that may stretch the whole 10x thing a bit… what kind of goals will we be setting 10 years from now?
Post updated: February 08, 2022
Using AI for customer service in your company is a definite method to save time and money. If you’re like most business owners, you’re constantly searching for fresh, creative ways to improve your enterprise. We’re here to inform you that improving AI customer service is a simple and rapid win.
If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
Here’s what’s new in our January 2023 Release Notes:
* Tables Columns Sorting Improved
* Reconcile Commits Count Between KPI Card and the Table
* Efficiency Tab Improvements and Efficiency KPI Cards Align
